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15
CITATION.cff
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@ -8,7 +8,7 @@ message: 'To cite package "FreesearchR" in publications use:'
type: software type: software
license: AGPL-3.0-or-later license: AGPL-3.0-or-later
title: 'FreesearchR: Easy data analysis for clinicians' title: 'FreesearchR: Easy data analysis for clinicians'
version: 26.1.1 version: 26.2.1
doi: 10.5281/zenodo.14527429 doi: 10.5281/zenodo.14527429
identifiers: identifiers:
- type: url - type: url
@ -474,7 +474,7 @@ references:
authors: authors:
- family-names: Lüdecke - family-names: Lüdecke
given-names: Daniel given-names: Daniel
email: d.luedecke@uke.de email: officialeasystats@gmail.com
orcid: https://orcid.org/0000-0002-8895-3206 orcid: https://orcid.org/0000-0002-8895-3206
- family-names: Makowski - family-names: Makowski
given-names: Dominique given-names: Dominique
@ -813,6 +813,9 @@ references:
given-names: Barret given-names: Barret
email: barret@posit.co email: barret@posit.co
orcid: https://orcid.org/0000-0001-9986-114X orcid: https://orcid.org/0000-0001-9986-114X
- family-names: Haughton
given-names: Shannon
email: shannon.l.haughton@gsk.com
- family-names: Hughes - family-names: Hughes
given-names: Ellis given-names: Ellis
email: ellis.h.hughes@gsk.com email: ellis.h.hughes@gsk.com
@ -821,6 +824,9 @@ references:
given-names: Alexandra given-names: Alexandra
email: alexandralauer1@gmail.com email: alexandralauer1@gmail.com
orcid: https://orcid.org/0000-0002-4191-6301 orcid: https://orcid.org/0000-0002-4191-6301
- family-names: François
given-names: Romain
email: romain@tada.science
- family-names: Seo - family-names: Seo
given-names: JooYoung given-names: JooYoung
email: jseo1005@illinois.edu email: jseo1005@illinois.edu
@ -921,7 +927,7 @@ references:
authors: authors:
- family-names: Damsbo - family-names: Damsbo
given-names: Andreas Gammelgaard given-names: Andreas Gammelgaard
email: agdamsbo@clin.au.dk email: andreas@gdamsbo.dk
orcid: https://orcid.org/0000-0002-7559-1154 orcid: https://orcid.org/0000-0002-7559-1154
- family-names: Egeler - family-names: Egeler
given-names: Paul given-names: Paul
@ -1101,11 +1107,14 @@ references:
email: asrini@pm.me email: asrini@pm.me
- family-names: Gorecki - family-names: Gorecki
given-names: Jan given-names: Jan
email: j.gorecki@wit.edu.pl
- family-names: Chirico - family-names: Chirico
given-names: Michael given-names: Michael
email: michaelchirico4@gmail.com
orcid: https://orcid.org/0000-0003-0787-087X orcid: https://orcid.org/0000-0003-0787-087X
- family-names: Hocking - family-names: Hocking
given-names: Toby given-names: Toby
email: toby.hocking@r-project.org
orcid: https://orcid.org/0000-0002-3146-0865 orcid: https://orcid.org/0000-0002-3146-0865
- family-names: Schwendinger - family-names: Schwendinger
given-names: Benjamin given-names: Benjamin

2
DESCRIPTION
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@ -1,6 +1,6 @@
Package: FreesearchR Package: FreesearchR
Title: Easy data analysis for clinicians Title: Easy data analysis for clinicians
Version: 26.1.2 Version: 26.2.1
Authors@R: c( Authors@R: c(
person("Andreas Gammelgaard", "Damsbo",email="agdamsbo@clin.au.dk", role = c("aut", "cre"), person("Andreas Gammelgaard", "Damsbo",email="agdamsbo@clin.au.dk", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-7559-1154")), comment = c(ORCID = "0000-0002-7559-1154")),

13
NEWS.md
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@ -1,3 +1,16 @@
# FreesearchR 26.2.1
This update is mainly focused on polishing, fixes and small additions to make the app more intuitive.
*NEW* Link on landing page to quickly go to data loading.
*NEW* Allow custom data set limit loading large data files, while tightening default limits. This secures the server, but also allows for unlimited use when run locally or from a custom server in a future implementation. The groundwork is place now.
*NEW* Hidden options and info alert when trying to analyse missing in complete dataset. The sub panel may be hidden in future iterations for this case.
Updated dependencies. Updated to latest R for building and testing. Using the new Air package for code formatting.
# FreesearchR 26.1.2 # FreesearchR 26.1.2
Rebuild 26.1.1 Rebuild 26.1.1

2
R/app_version.R
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@ -1 +1 @@
app_version <- function()'26.1.2' app_version <- function()'26.2.1'

132
R/helpers.R
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@ -50,7 +50,7 @@ write_quarto <- function(data, ...) {
) )
} }
write_rmd <- function(data, ..., params.args=NULL) { write_rmd <- function(data, ..., params.args = NULL) {
# Exports data to temporary location # Exports data to temporary location
# #
# I assume this is more secure than putting it in the www folder and deleting # I assume this is more secure than putting it in the www folder and deleting
@ -65,7 +65,10 @@ write_rmd <- function(data, ..., params.args=NULL) {
## Ref: https://github.com/quarto-dev/quarto-cli/discussions/4041 ## Ref: https://github.com/quarto-dev/quarto-cli/discussions/4041
## Outputs to the same as the .qmd file ## Outputs to the same as the .qmd file
rmarkdown::render( rmarkdown::render(
params = modifyList(list(data.file = "web_data.rds",version=app_version()),params.args), params = modifyList(
list(data.file = "web_data.rds", version = app_version()),
params.args
),
# execute_params = list(data.file = temp), # execute_params = list(data.file = temp),
... ...
) )
@ -133,12 +136,7 @@ argsstring2list <- function(string) {
factorize <- function(data, vars) { factorize <- function(data, vars) {
if (!is.null(vars)) { if (!is.null(vars)) {
data |> data |>
dplyr::mutate( dplyr::mutate(dplyr::across(dplyr::all_of(vars), REDCapCAST::as_factor))
dplyr::across(
dplyr::all_of(vars),
REDCapCAST::as_factor
)
)
} else { } else {
data data
} }
@ -171,32 +169,30 @@ dummy_Imports <- function() {
#' @returns data #' @returns data
#' @export #' @export
#' #'
file_export <- function(data, output.format = c("df", "teal", "list"), filename, ...) { file_export <- function(data,
output.format = c("df", "teal", "list"),
filename,
...) {
output.format <- match.arg(output.format) output.format <- match.arg(output.format)
filename <- gsub("-", "_", filename) filename <- gsub("-", "_", filename)
if (output.format == "teal") { if (output.format == "teal") {
out <- within( out <- within(teal_data(), {
teal_data(), assign(
{ name,
assign(name, value |> value |>
dplyr::bind_cols(.name_repair = "unique_quiet") |> dplyr::bind_cols(.name_repair = "unique_quiet") |>
default_parsing()) default_parsing()
}, )
value = data, }, value = data, name = filename)
name = filename
)
datanames(out) <- filename datanames(out) <- filename
} else if (output.format == "df") { } else if (output.format == "df") {
out <- data |> out <- data |>
default_parsing() default_parsing()
} else if (output.format == "list") { } else if (output.format == "list") {
out <- list( out <- list(data = data, name = filename)
data = data,
name = filename
)
out <- c(out, ...) out <- c(out, ...)
} }
@ -231,7 +227,8 @@ default_parsing <- function(data) {
remove_nested_list() |> remove_nested_list() |>
REDCapCAST::parse_data() |> REDCapCAST::parse_data() |>
REDCapCAST::as_factor() |> REDCapCAST::as_factor() |>
REDCapCAST::numchar2fct(numeric.threshold = 8, character.throshold = 10) |> REDCapCAST::numchar2fct(numeric.threshold = 8,
character.throshold = 10) |>
REDCapCAST::as_logical() |> REDCapCAST::as_logical() |>
REDCapCAST::fct_drop() REDCapCAST::fct_drop()
@ -295,9 +292,11 @@ remove_empty_attr <- function(data) {
#' @examples #' @examples
#' data.frame(a = 1:10, b = NA, c = c(2, NA)) |> remove_empty_cols(cutoff = .5) #' data.frame(a = 1:10, b = NA, c = c(2, NA)) |> remove_empty_cols(cutoff = .5)
remove_empty_cols <- function(data, cutoff = .7) { remove_empty_cols <- function(data, cutoff = .7) {
filter <- apply(X = data, MARGIN = 2, FUN = \(.x){ filter <- apply(X = data,
sum(as.numeric(!is.na(.x))) / length(.x) MARGIN = 2,
}) >= cutoff FUN = \(.x) {
sum(as.numeric(!is.na(.x))) / length(.x)
}) >= cutoff
data[filter] data[filter]
} }
@ -357,14 +356,25 @@ missing_fraction <- function(data) {
#' sample(c(1:8, NA), 20, TRUE) #' sample(c(1:8, NA), 20, TRUE)
#' ) |> data_description() #' ) |> data_description()
data_description <- function(data, data_text = "Data") { data_description <- function(data, data_text = "Data") {
data <- if (shiny::is.reactive(data)) data() else data data <- if (shiny::is.reactive(data))
data()
else
data
n <- nrow(data) n <- nrow(data)
n_var <- ncol(data) n_var <- ncol(data)
n_complete <- sum(complete.cases(data)) n_complete <- sum(complete.cases(data))
p_complete <- signif(100 * n_complete / n, 3) p_complete <- signif(100 * n_complete / n, 3)
glue::glue(i18n$t("{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.")) if (is.null(data)) {
i18n$t("No data present.")
} else {
glue::glue(
i18n$t(
"{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases."
)
)
}
# sprintf( # sprintf(
# "%s has %s observations and %s variables, with %s (%s%%) complete cases.", # "%s has %s observations and %s variables, with %s (%s%%) complete cases.",
# data_text, # data_text,
@ -473,7 +483,8 @@ if_not_missing <- function(data, default = NULL) {
#' ) |> merge_expression() #' ) |> merge_expression()
merge_expression <- function(data) { merge_expression <- function(data) {
Reduce( Reduce(
f = function(x, y) rlang::expr(!!x %>% !!y), f = function(x, y)
rlang::expr(!!x %>% !!y),
x = data x = data
) )
} }
@ -497,7 +508,8 @@ merge_expression <- function(data) {
pipe_string <- function(data, collapse = "|>\n") { pipe_string <- function(data, collapse = "|>\n") {
if (is.list(data)) { if (is.list(data)) {
Reduce( Reduce(
f = function(x, y) glue::glue("{x}{collapse}{y}"), f = function(x, y)
glue::glue("{x}{collapse}{y}"),
x = data x = data
) )
} else { } else {
@ -521,10 +533,15 @@ pipe_string <- function(data, collapse = "|>\n") {
#' merge_expression() |> #' merge_expression() |>
#' expression_string() #' expression_string()
expression_string <- function(data, assign.str = "") { expression_string <- function(data, assign.str = "") {
exp.str <- if (is.call(data)) deparse(data) else data exp.str <- if (is.call(data))
deparse(data)
else
data
out <- paste0(assign.str, gsub("%>%", "|>\n", paste(gsub('"', "'", paste(exp.str, collapse = "")), collapse = ""))) out <- paste0(assign.str, gsub("%>%", "|>\n", paste(gsub(
out <- collapse_spaces(out,preserve_newlines = FALSE) '"', "'", paste(exp.str, collapse = "")
), collapse = "")))
out <- collapse_spaces(out, preserve_newlines = FALSE)
gsub("`", "", out) gsub("`", "", out)
} }
@ -628,10 +645,16 @@ remove_nested_list <- function(data) {
#' rlang::expr(FreesearchR::set_column_label(label = !!ls3)) |> expression_string() #' rlang::expr(FreesearchR::set_column_label(label = !!ls3)) |> expression_string()
set_column_label <- function(data, label, overwrite = TRUE) { set_column_label <- function(data, label, overwrite = TRUE) {
purrr::imap(data, function(.data, .name) { purrr::imap(data, function(.data, .name) {
ls <- if (is.list(label)) unlist(label) else label ls <- if (is.list(label))
unlist(label)
else
label
ls[ls == ""] <- NA ls[ls == ""] <- NA
if (.name %in% names(ls)) { if (.name %in% names(ls)) {
out <- REDCapCAST::set_attr(.data, unname(ls[.name]), attr = "label", overwrite = overwrite) out <- REDCapCAST::set_attr(.data,
unname(ls[.name]),
attr = "label",
overwrite = overwrite)
remove_empty_attr(out) remove_empty_attr(out)
} else { } else {
.data .data
@ -682,11 +705,8 @@ append_column <- function(data, column, name, index = "right") {
} }
new_df <- setNames(data.frame(column), name) new_df <- setNames(data.frame(column), name)
list( list(data[seq_len(index - 1)], new_df, if (!index > ncol(data))
data[seq_len(index - 1)], data[index:ncol(data)]) |>
new_df,
if (!index > ncol(data)) data[index:ncol(data)]
) |>
dplyr::bind_cols() dplyr::bind_cols()
} }
@ -711,7 +731,7 @@ is_identical_to_previous <- function(data, no.name = TRUE) {
lagged <- c(FALSE, data[seq_len(length(data) - 1)]) lagged <- c(FALSE, data[seq_len(length(data) - 1)])
} }
vapply(seq_len(length(data)), \(.x){ vapply(seq_len(length(data)), \(.x) {
if (isTRUE(no.name)) { if (isTRUE(no.name)) {
identical(unname(lagged[.x]), unname(data[.x])) identical(unname(lagged[.x]), unname(data[.x]))
} else { } else {
@ -730,8 +750,11 @@ is_identical_to_previous <- function(data, no.name = TRUE) {
#' #'
#' @examples #' @examples
#' c("foo bar", "fooBar21", "!!Foo'B'a-r", "foo_bar", "F OO bar") |> simple_snake() #' c("foo bar", "fooBar21", "!!Foo'B'a-r", "foo_bar", "F OO bar") |> simple_snake()
simple_snake <- function(data){ simple_snake <- function(data) {
gsub("[\\s+]","_",gsub("[^\\w\\s:-]", "", tolower(data), perl=TRUE), perl=TRUE) gsub("[\\s+]",
"_",
gsub("[^\\w\\s:-]", "", tolower(data), perl = TRUE),
perl = TRUE)
} }
#' Data type assessment. #' Data type assessment.
@ -768,7 +791,8 @@ data_type <- function(data) {
out <- "empty" out <- "empty"
} else if (l_unique < 2) { } else if (l_unique < 2) {
out <- "monotone" out <- "monotone"
} else if (any(c("factor", "logical") %in% cl_d) | l_unique == 2) { } else if (any(c("factor", "logical") %in% cl_d) |
l_unique == 2) {
if (identical("logical", cl_d) | l_unique == 2) { if (identical("logical", cl_d) | l_unique == 2) {
out <- "dichotomous" out <- "dichotomous"
} else { } else {
@ -804,13 +828,17 @@ data_type <- function(data) {
#' data_types() #' data_types()
data_types <- function() { data_types <- function() {
list( list(
"empty" = list(descr="Variable of all NAs",classes="Any class"), "empty" = list(descr = "Variable of all NAs", classes = "Any class"),
"monotone" = list(descr="Variable with only one unique value",classes="Any class"), "monotone" = list(descr = "Variable with only one unique value", classes =
"dichotomous" = list(descr="Variable with only two unique values",classes="Any class"), "Any class"),
"categorical"= list(descr="Factor variable",classes="factor (ordered or unordered)"), "dichotomous" = list(descr = "Variable with only two unique values", classes =
"text"= list(descr="Character variable",classes="character"), "Any class"),
"datetime"= list(descr="Variable of time, date or datetime values",classes="hms, Date, POSIXct and POSIXt"), "categorical" = list(descr = "Factor variable", classes = "factor (ordered or unordered)"),
"continuous"= list(descr="Numeric variable",classes="numeric, integer or double"), "text" = list(descr = "Character variable", classes = "character"),
"unknown"= list(descr="Anything not falling within the previous",classes="Any other class") "datetime" = list(descr = "Variable of time, date or datetime values", classes =
"hms, Date, POSIXct and POSIXt"),
"continuous" = list(descr = "Numeric variable", classes = "numeric, integer or double"),
"unknown" = list(descr = "Anything not falling within the previous", classes =
"Any other class")
) )
} }

2
R/hosted_version.R
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@ -1 +1 @@
hosted_version <- function()'v26.1.2-260112' hosted_version <- function()'v26.2.1-260223'

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R/sysdata.rda
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1
R/translate.R
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@ -7,4 +7,3 @@ language_choices <- function() {
# "🇸🇪 Svenska" = "sv" # "🇸🇪 Svenska" = "sv"
) )
} }

203
R/ui_elements.R
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@ -25,7 +25,7 @@ ui_elements <- function(selection) {
## Default just output "NULL" ## Default just output "NULL"
## This could probably be achieved more legantly, but this works. ## This could probably be achieved more legantly, but this works.
dev_banner(), dev_banner(),
landing_page_ui(i18n=i18n), landing_page_ui(i18n = i18n),
# shiny::column(width = 2), # shiny::column(width = 2),
# shiny::column( # shiny::column(
# width = 8, # width = 8,
@ -68,7 +68,11 @@ ui_elements <- function(selection) {
), ),
# shiny::tags$script('document.querySelector("#source div").style.width = "100%"'), # shiny::tags$script('document.querySelector("#source div").style.width = "100%"'),
## Update this to change depending on run locally or hosted ## Update this to change depending on run locally or hosted
shiny::helpText(i18n$t("Upload a file, get data directly from REDCap or use local or sample data.")), shiny::helpText(
i18n$t(
"Upload a file, get data directly from REDCap or use local or sample data."
)
),
shiny::br(), shiny::br(),
shiny::br(), shiny::br(),
shiny::conditionalPanel( shiny::conditionalPanel(
@ -77,7 +81,11 @@ ui_elements <- function(selection) {
id = "file_import", id = "file_import",
layout_params = "dropdown", layout_params = "dropdown",
# title = "Choose a datafile to upload", # title = "Choose a datafile to upload",
file_extensions = c(".csv", ".tsv", ".txt", ".xls", ".xlsx", ".rds", ".ods", ".dta") file_extensions = c(".csv", ".tsv", ".txt", ".xls", ".xlsx", ".rds", ".ods", ".dta"),
limit_default = global_freesearchR$data_limit_default,
limit_lower = global_freesearchR$data_limit_lower,
limit_upper = global_freesearchR$data_limit_upper
) )
), ),
shiny::conditionalPanel( shiny::conditionalPanel(
@ -90,17 +98,15 @@ ui_elements <- function(selection) {
# shiny::HTML(i18n$t("<p>The <em><strong>FreesearchR</strong></em> app only stores data for analyses, but please only use with sensitive data when running locally. <a href='https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine'>Read more here</a></p>")), # shiny::HTML(i18n$t("<p>The <em><strong>FreesearchR</strong></em> app only stores data for analyses, but please only use with sensitive data when running locally. <a href='https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine'>Read more here</a></p>")),
# dismissible = TRUE # dismissible = TRUE
# ), # ),
m_redcap_readUI( m_redcap_readUI(id = "redcap_import", title = "")
id = "redcap_import",
title = ""
)
), ),
shiny::conditionalPanel( shiny::conditionalPanel(
condition = "input.source=='env'", condition = "input.source=='env'",
import_globalenv_ui( import_globalenv_ui(
id = "env", id = "env",
title = NULL, title = NULL,
packages = c("NHANES", "stRoke", "datasets", "MASS") packages = c("NHANES", "stRoke", "datasets", "MASS"),
globalenv = global_freesearchR$include_globalenv
) )
), ),
# shiny::conditionalPanel( # shiny::conditionalPanel(
@ -136,7 +142,11 @@ ui_elements <- function(selection) {
format = shinyWidgets::wNumbFormat(decimals = 0), format = shinyWidgets::wNumbFormat(decimals = 0),
color = datamods:::get_primary_color() color = datamods:::get_primary_color()
), ),
shiny::helpText(i18n$t("At 0, only complete variables are included; at 100, all variables are included.")), shiny::helpText(
i18n$t(
"At 0, only complete variables are included; at 100, all variables are included."
)
),
shiny::br() shiny::br()
), ),
shiny::column( shiny::column(
@ -185,7 +195,9 @@ ui_elements <- function(selection) {
width = 9, width = 9,
shiny::uiOutput(outputId = "data_info", inline = TRUE), shiny::uiOutput(outputId = "data_info", inline = TRUE),
shiny::tags$p( shiny::tags$p(
i18n$t("Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters.") i18n$t(
"Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters."
)
) )
), ),
shiny::column( shiny::column(
@ -221,16 +233,18 @@ ui_elements <- function(selection) {
shiny::column( shiny::column(
width = 3, width = 3,
shiny::tags$h6(i18n$t("Filter data types")), shiny::tags$h6(i18n$t("Filter data types")),
shiny::uiOutput( shiny::uiOutput(outputId = "column_filter"),
outputId = "column_filter"
),
## This needs to run in server for translation ## This needs to run in server for translation
shiny::helpText("Read more on how ", tags$a( shiny::helpText(
"data types", "Read more on how ",
href = "https://agdamsbo.github.io/FreesearchR/articles/data-types.html", tags$a(
target = "_blank", "data types",
rel = "noopener noreferrer" href = "https://agdamsbo.github.io/FreesearchR/articles/data-types.html",
), " are defined."), target = "_blank",
rel = "noopener noreferrer"
),
" are defined."
),
validation_ui("validation_var"), validation_ui("validation_var"),
shiny::br(), shiny::br(),
shiny::br(), shiny::br(),
@ -250,21 +264,26 @@ ui_elements <- function(selection) {
title = i18n$t("Edit and create data"), title = i18n$t("Edit and create data"),
icon = shiny::icon("file-pen"), icon = shiny::icon("file-pen"),
tags$h3(i18n$t("Subset, rename and convert variables")), tags$h3(i18n$t("Subset, rename and convert variables")),
fluidRow( fluidRow(shiny::column(
shiny::column( width = 9, shiny::tags$p(
width = 9, i18n$t(
shiny::tags$p( "Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.)."
i18n$t("Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.)."), ),
i18n$t("There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data."), i18n$t(
i18n$t("Please note that data modifications are applied before any filtering.") "There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data."
),
i18n$t(
"Please note that data modifications are applied before any filtering."
) )
) )
), )),
update_variables_ui("modal_variables"), update_variables_ui("modal_variables"),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$h4(i18n$t("Advanced data manipulation")), shiny::tags$h4(i18n$t("Advanced data manipulation")),
shiny::tags$p(i18n$t("Below options allow more advanced varaible manipulations.")), shiny::tags$p(
i18n$t("Below options allow more advanced varaible manipulations.")
),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$br(), shiny::tags$br(),
shiny::fluidRow( shiny::fluidRow(
@ -276,7 +295,9 @@ ui_elements <- function(selection) {
width = "100%" width = "100%"
), ),
shiny::tags$br(), shiny::tags$br(),
shiny::helpText(i18n$t("Reorder or rename the levels of factor/categorical variables.")), shiny::helpText(
i18n$t("Reorder or rename the levels of factor/categorical variables.")
),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$br() shiny::tags$br()
), ),
@ -288,7 +309,11 @@ ui_elements <- function(selection) {
width = "100%" width = "100%"
), ),
shiny::tags$br(), shiny::tags$br(),
shiny::helpText(i18n$t("Create factor/categorical variable from a continous variable (number/date/time).")), shiny::helpText(
i18n$t(
"Create factor/categorical variable from a continous variable (number/date/time)."
)
),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$br() shiny::tags$br()
), ),
@ -300,7 +325,9 @@ ui_elements <- function(selection) {
width = "100%" width = "100%"
), ),
shiny::tags$br(), shiny::tags$br(),
shiny::helpText(i18n$t("Split a text column by a recognised delimiter.")), shiny::helpText(i18n$t(
"Split a text column by a recognised delimiter."
)),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$br() shiny::tags$br()
), ),
@ -312,16 +339,18 @@ ui_elements <- function(selection) {
width = "100%" width = "100%"
), ),
shiny::tags$br(), shiny::tags$br(),
shiny::helpText(i18n$t("Create a new variable based on an R-expression.")), shiny::helpText(i18n$t(
"Create a new variable based on an R-expression."
)),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$br() shiny::tags$br()
) )
), ),
tags$h4(i18n$t("Compare modified data to original")), tags$h4(i18n$t("Compare modified data to original")),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$p( shiny::tags$p(i18n$t(
i18n$t("Raw print of the original vs the modified data.") "Raw print of the original vs the modified data."
), )),
shiny::tags$br(), shiny::tags$br(),
shiny::fluidRow( shiny::fluidRow(
shiny::column( shiny::column(
@ -342,7 +371,11 @@ ui_elements <- function(selection) {
width = "100%" width = "100%"
), ),
shiny::tags$br(), shiny::tags$br(),
shiny::helpText(i18n$t("Reset to original imported dataset. Careful! There is no un-doing.")), shiny::helpText(
i18n$t(
"Reset to original imported dataset. Careful! There is no un-doing."
)
),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$br() shiny::tags$br()
) )
@ -388,7 +421,11 @@ ui_elements <- function(selection) {
# ), # ),
shiny::uiOutput("detail_level"), shiny::uiOutput("detail_level"),
shiny::uiOutput("strat_var"), shiny::uiOutput("strat_var"),
shiny::helpText(i18n$t("Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list.")), shiny::helpText(
i18n$t(
"Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list."
)
),
shiny::conditionalPanel( shiny::conditionalPanel(
condition = "input.strat_var!='none'", condition = "input.strat_var!='none'",
shiny::radioButtons( shiny::radioButtons(
@ -396,10 +433,7 @@ ui_elements <- function(selection) {
label = i18n$t("Compare strata?"), label = i18n$t("Compare strata?"),
selected = "no", selected = "no",
inline = TRUE, inline = TRUE,
choices = list( choices = list("No" = "no", "Yes" = "yes")
"No" = "no",
"Yes" = "yes"
)
), ),
# shiny::helpText(i18n$t("Option to perform statistical comparisons between strata in baseline table.")), # shiny::helpText(i18n$t("Option to perform statistical comparisons between strata in baseline table.")),
shiny::br(), shiny::br(),
@ -408,10 +442,7 @@ ui_elements <- function(selection) {
label = i18n$t("Include group differences"), label = i18n$t("Include group differences"),
selected = "no", selected = "no",
inline = TRUE, inline = TRUE,
choices = list( choices = list("No" = "no", "Yes" = "yes")
"No" = "no",
"Yes" = "yes"
)
) )
), ),
shiny::br(), shiny::br(),
@ -422,7 +453,9 @@ ui_elements <- function(selection) {
icon = shiny::icon("calculator"), icon = shiny::icon("calculator"),
disabled = TRUE disabled = TRUE
), ),
shiny::helpText(i18n$t("Press 'Evaluate' to create the comparison table.")) shiny::helpText(i18n$t(
"Press 'Evaluate' to create the comparison table."
))
) )
) )
), ),
@ -444,7 +477,11 @@ ui_elements <- function(selection) {
title = "Settings", title = "Settings",
icon = bsicons::bs_icon("bounding-box"), icon = bsicons::bs_icon("bounding-box"),
shiny::uiOutput("outcome_var_cor"), shiny::uiOutput("outcome_var_cor"),
shiny::helpText(i18n$t("To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.")), shiny::helpText(
i18n$t(
"To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'."
)
),
shiny::br(), shiny::br(),
shinyWidgets::noUiSliderInput( shinyWidgets::noUiSliderInput(
inputId = "cor_cutoff", inputId = "cor_cutoff",
@ -456,24 +493,22 @@ ui_elements <- function(selection) {
format = shinyWidgets::wNumbFormat(decimals = 2), format = shinyWidgets::wNumbFormat(decimals = 2),
color = datamods:::get_primary_color() color = datamods:::get_primary_color()
), ),
shiny::helpText(i18n$t("Set the cut-off for considered 'highly correlated'.")) shiny::helpText(i18n$t(
"Set the cut-off for considered 'highly correlated'."
))
) )
) )
), ),
data_correlations_ui(id = "correlations", height = 600) data_correlations_ui(id = "correlations", height = 600)
) )
), ),
do.call( do.call(bslib::nav_panel, c(
bslib::nav_panel, list(
c( title = i18n$t("Missings"),
list( icon = bsicons::bs_icon("x-circle")
title = i18n$t("Missings"), ),
icon = bsicons::bs_icon("x-circle") data_missings_ui(id = "missingness", validation_ui("validation_mcar"))
), ))
data_missings_ui(id = "missingness",
validation_ui("validation_mcar"))
)
)
), ),
############################################################################## ##############################################################################
######### #########
@ -508,10 +543,7 @@ ui_elements <- function(selection) {
title = i18n$t("Regression"), title = i18n$t("Regression"),
icon = shiny::icon("calculator"), icon = shiny::icon("calculator"),
value = "nav_analyses", value = "nav_analyses",
do.call( do.call(bslib::navset_card_tab, regression_ui("regression"))
bslib::navset_card_tab,
regression_ui("regression")
)
), ),
############################################################################## ##############################################################################
######### #########
@ -533,7 +565,11 @@ ui_elements <- function(selection) {
shiny::column( shiny::column(
width = 6, width = 6,
shiny::h4(i18n$t("Report")), shiny::h4(i18n$t("Report")),
shiny::helpText(i18n$t("Choose your favourite output file format for further work, and download, when the analyses are done.")), shiny::helpText(
i18n$t(
"Choose your favourite output file format for further work, and download, when the analyses are done."
)
),
shiny::br(), shiny::br(),
shiny::br(), shiny::br(),
shiny::selectInput( shiny::selectInput(
@ -561,7 +597,9 @@ ui_elements <- function(selection) {
shiny::column( shiny::column(
width = 6, width = 6,
shiny::h4("Data"), shiny::h4("Data"),
shiny::helpText("Choose your favourite output data format to download the modified data."), shiny::helpText(
"Choose your favourite output data format to download the modified data."
),
shiny::br(), shiny::br(),
shiny::br(), shiny::br(),
shiny::selectInput( shiny::selectInput(
@ -588,16 +626,27 @@ ui_elements <- function(selection) {
shiny::br(), shiny::br(),
shiny::br(), shiny::br(),
shiny::h4("Code snippets"), shiny::h4("Code snippets"),
shiny::tags$p("Below are the code bits used to create the final data set and the main analyses."), shiny::tags$p(
shiny::tags$p("This can be used as a starting point for learning to code and for reproducibility."), "Below are the code bits used to create the final data set and the main analyses."
shiny::tagList(
lapply(
paste0("code_", c(
"import", "format", "data", "variables", "filter", "table1", "univariable", "multivariable"
)),
\(.x)shiny::htmlOutput(outputId = .x)
)
), ),
shiny::tags$p(
"This can be used as a starting point for learning to code and for reproducibility."
),
shiny::tagList(lapply(
paste0(
"code_",
c(
"import",
"format",
"data",
"variables",
"filter",
"table1",
"univariable",
"multivariable"
)
), \(.x)shiny::htmlOutput(outputId = .x)
)),
shiny::tags$br(), shiny::tags$br(),
shiny::br() shiny::br()
), ),
@ -613,7 +662,8 @@ ui_elements <- function(selection) {
# shiny::img(shiny::icon("book")), # shiny::img(shiny::icon("book")),
shiny::tags$a( shiny::tags$a(
href = "https://redcap.au.dk/surveys/?s=JPCLPTXYDKFA8DA8", href = "https://redcap.au.dk/surveys/?s=JPCLPTXYDKFA8DA8",
"Feedback", shiny::icon("arrow-up-right-from-square"), "Feedback",
shiny::icon("arrow-up-right-from-square"),
target = "_blank", target = "_blank",
rel = "noopener noreferrer" rel = "noopener noreferrer"
) )
@ -627,7 +677,8 @@ ui_elements <- function(selection) {
# shiny::img(shiny::icon("book")), # shiny::img(shiny::icon("book")),
shiny::tags$a( shiny::tags$a(
href = "https://agdamsbo.github.io/FreesearchR/", href = "https://agdamsbo.github.io/FreesearchR/",
"Docs", shiny::icon("arrow-up-right-from-square"), "Docs",
shiny::icon("arrow-up-right-from-square"),
target = "_blank", target = "_blank",
rel = "noopener noreferrer" rel = "noopener noreferrer"
) )

338
R/update-factor-ext.R
View file

@ -78,7 +78,10 @@ update_factor_ui <- function(id) {
), ),
actionButton( actionButton(
inputId = ns("create"), inputId = ns("create"),
label = tagList(phosphoricons::ph("arrow-clockwise"), i18n$t("Update factor variable")), label = tagList(
phosphoricons::ph("arrow-clockwise"),
i18n$t("Update factor variable")
),
class = "btn-outline-primary" class = "btn-outline-primary"
) )
), ),
@ -97,154 +100,136 @@ update_factor_ui <- function(id) {
#' #'
#' @rdname update-factor #' @rdname update-factor
update_factor_server <- function(id, data_r = reactive(NULL)) { update_factor_server <- function(id, data_r = reactive(NULL)) {
moduleServer( moduleServer(id, function(input, output, session) {
id, rv <- reactiveValues(data = NULL, data_grid = NULL)
function(input, output, session) {
rv <- reactiveValues(data = NULL, data_grid = NULL)
bindEvent(observe({ bindEvent(observe({
data <- data_r() data <- data_r()
rv$data <- data rv$data <- data
vars_factor <- vapply(data, is.factor, logical(1)) vars_factor <- vapply(data, is.factor, logical(1))
vars_factor <- names(vars_factor)[vars_factor] vars_factor <- names(vars_factor)[vars_factor]
updateVirtualSelect( updateVirtualSelect(
inputId = "variable", inputId = "variable",
choices = vars_factor, choices = vars_factor,
selected = if (isTruthy(input$variable)) input$variable else vars_factor[1] selected = if (isTruthy(input$variable))
) input$variable
}), data_r(), input$hidden) else
vars_factor[1]
)
}), data_r(), input$hidden)
observeEvent(input$variable, { observeEvent(input$variable, {
data <- req(data_r()) data <- req(data_r())
variable <- req(input$variable) variable <- req(input$variable)
grid <- as.data.frame(table(data[[variable]])) grid <- as.data.frame(table(data[[variable]]))
rv$data_grid <- grid rv$data_grid <- grid
})
observeEvent(input$sort_levels, {
if (input$sort_levels %% 2 == 1) {
decreasing <- FALSE
label <- tagList(phosphoricons::ph("sort-descending"),
i18n$t("Sort by Levels"))
} else {
decreasing <- TRUE
label <- tagList(phosphoricons::ph("sort-ascending"),
i18n$t("Sort by Levels"))
}
updateActionButton(inputId = "sort_levels", label = label)
rv$data_grid <- rv$data_grid[order(rv$data_grid[[1]], decreasing = decreasing), ]
})
observeEvent(input$sort_occurrences, {
if (input$sort_occurrences %% 2 == 1) {
decreasing <- FALSE
label <- tagList(phosphoricons::ph("sort-descending"),
i18n$t("Sort by count"))
} else {
decreasing <- TRUE
label <- tagList(phosphoricons::ph("sort-ascending"),
i18n$t("Sort by count"))
}
updateActionButton(inputId = "sort_occurrences", label = label)
rv$data_grid <- rv$data_grid[order(rv$data_grid[[2]], decreasing = decreasing), ]
})
output$grid <- renderDatagrid({
req(rv$data_grid)
gridTheme <- getOption("datagrid.theme")
if (length(gridTheme) < 1) {
datamods:::apply_grid_theme()
}
on.exit(toastui::reset_grid_theme())
data <- rv$data_grid
data <- add_var_toset(data, "Var1", "New label")
grid <- datagrid(
data = data,
draggable = TRUE,
sortable = FALSE,
data_as_input = TRUE
)
grid <- grid_columns(
grid,
columns = c("Var1", "Var1_toset", "Freq"),
header = c(i18n$t("Levels"), "New label", i18n$t("Count"))
)
grid <- grid_colorbar(
grid,
column = "Freq",
label_outside = TRUE,
label_width = "30px",
background = "#D8DEE9",
bar_bg = datamods:::get_primary_color(),
from = c(0, max(rv$data_grid$Freq) + 1)
)
grid <- toastui::grid_style_column(grid = grid,
column = "Var1_toset",
fontStyle = "italic")
grid <- toastui::grid_editor(grid = grid,
column = "Var1_toset",
type = "text")
grid
})
data_updated_r <- reactive({
data <- req(data_r())
variable <- req(input$variable)
grid <- req(input$grid_data)
parameters <- list(
variable = variable,
new_variable = isTRUE(input$new_var) |
any(grid[["Var1_toset"]] == "New label"),
new_levels = as.character(grid[["Var1"]]),
new_labels = as.character(grid[["Var1_toset"]]),
ignore = "New label"
)
data <- tryCatch({
rlang::exec(factor_new_levels_labels,
!!!modifyList(parameters, val = list(data = data)))
}, error = function(err) {
showNotification(paste(
"We encountered the following error creating the new factor:",
err
),
type = "err")
}) })
observeEvent(input$sort_levels, { # browser()
if (input$sort_levels %% 2 == 1) { code <- rlang::call2("factor_new_levels_labels", !!!parameters, .ns = "FreesearchR")
decreasing <- FALSE attr(data, "code") <- code
label <- tagList(
phosphoricons::ph("sort-descending"),
i18n$t("Sort by Levels")
)
} else {
decreasing <- TRUE
label <- tagList(
phosphoricons::ph("sort-ascending"),
i18n$t("Sort by Levels")
)
}
updateActionButton(inputId = "sort_levels", label = label)
rv$data_grid <- rv$data_grid[order(rv$data_grid[[1]], decreasing = decreasing), ]
})
observeEvent(input$sort_occurrences, { data
if (input$sort_occurrences %% 2 == 1) { })
decreasing <- FALSE
label <- tagList(
phosphoricons::ph("sort-descending"),
i18n$t("Sort by count")
)
} else {
decreasing <- TRUE
label <- tagList(
phosphoricons::ph("sort-ascending"),
i18n$t("Sort by count")
)
}
updateActionButton(inputId = "sort_occurrences", label = label)
rv$data_grid <- rv$data_grid[order(rv$data_grid[[2]], decreasing = decreasing), ]
})
data_returned_r <- observeEvent(input$create, {
output$grid <- renderDatagrid({ rv$data <- data_updated_r()
req(rv$data_grid) })
gridTheme <- getOption("datagrid.theme") return(reactive(rv$data))
if (length(gridTheme) < 1) { })
datamods:::apply_grid_theme()
}
on.exit(toastui::reset_grid_theme())
data <- rv$data_grid
data <- add_var_toset(data, "Var1", "New label")
grid <- datagrid(
data = data,
draggable = TRUE,
sortable = FALSE,
data_as_input = TRUE
)
grid <- grid_columns(
grid,
columns = c("Var1", "Var1_toset", "Freq"),
header = c(i18n$t("Levels"), "New label", i18n$t("Count"))
)
grid <- grid_colorbar(
grid,
column = "Freq",
label_outside = TRUE,
label_width = "30px",
background = "#D8DEE9",
bar_bg = datamods:::get_primary_color(),
from = c(0, max(rv$data_grid$Freq) + 1)
)
grid <- toastui::grid_style_column(
grid = grid,
column = "Var1_toset",
fontStyle = "italic"
)
grid <- toastui::grid_editor(
grid = grid,
column = "Var1_toset",
type = "text"
)
grid
})
data_updated_r <- reactive({
data <- req(data_r())
variable <- req(input$variable)
grid <- req(input$grid_data)
parameters <- list(
variable = variable,
new_variable = isTRUE(input$new_var) | any(grid[["Var1_toset"]] == "New label"),
new_levels = as.character(grid[["Var1"]]),
new_labels = as.character(grid[["Var1_toset"]]),
ignore = "New label"
)
data <- tryCatch(
{
rlang::exec(
factor_new_levels_labels,
!!!modifyList(parameters,
val = list(data = data)
)
)
},
error = function(err) {
showNotification(paste("We encountered the following error creating the new factor:", err), type = "err")
}
)
# browser()
code <- rlang::call2(
"factor_new_levels_labels",
!!!parameters,
.ns = "FreesearchR"
)
attr(data, "code") <- code
data
})
data_returned_r <- observeEvent(input$create, {
rv$data <- data_updated_r()
})
return(reactive(rv$data))
}
)
} }
#' Simple function to apply new levels and/or labels to factor #' Simple function to apply new levels and/or labels to factor
@ -261,13 +246,12 @@ update_factor_server <- function(id, data_r = reactive(NULL)) {
#' data_n <- mtcars #' data_n <- mtcars
#' data_n$cyl <- factor(data_n$cyl) #' data_n$cyl <- factor(data_n$cyl)
#' factor_new_levels_labels(data_n, "cyl", new_labels = c("four", "New label", "New label")) #' factor_new_levels_labels(data_n, "cyl", new_labels = c("four", "New label", "New label"))
factor_new_levels_labels <- function( factor_new_levels_labels <- function(data,
data, variable,
variable, new_variable = TRUE,
new_variable = TRUE, new_levels = NULL,
new_levels = NULL, new_labels = NULL,
new_labels = NULL, ignore = "New label") {
ignore = "New label") {
if (!is.factor(data[[variable]])) { if (!is.factor(data[[variable]])) {
return(data) return(data)
} }
@ -280,21 +264,19 @@ factor_new_levels_labels <- function(
new_labels <- labels(data[[variable]]) new_labels <- labels(data[[variable]])
} }
with_level <- factor( with_level <- factor(as.character(data[[variable]]), levels = new_levels)
as.character(data[[variable]]), with_label <- factor(with_level,
levels = new_levels labels = ifelse(new_labels == "New label", new_levels, new_labels))
)
with_label <- factor(
with_level,
labels = ifelse(new_labels == "New label", new_levels, new_labels)
)
if (isTRUE(new_variable)) { if (isTRUE(new_variable)) {
append_column( append_column(
data = data, data = data,
column = with_label, column = with_label,
name = unique_names(new = paste0(variable, "_updated"), existing = names(data)) name = unique_names(
new = paste0(variable, "_updated"),
existing = names(data)
)
) )
} else { } else {
data[[variable]] <- with_label data[[variable]] <- with_label
@ -303,7 +285,6 @@ factor_new_levels_labels <- function(
} }
#' @inheritParams shiny::modalDialog #' @inheritParams shiny::modalDialog
#' @export #' @export
#' #'
@ -317,17 +298,23 @@ modal_update_factor <- function(id,
size = "l", size = "l",
footer = NULL) { footer = NULL) {
ns <- NS(id) ns <- NS(id)
showModal(modalDialog( showModal(
title = tagList(title, datamods:::button_close_modal()), modalDialog(
update_factor_ui(id), title = tagList(title, datamods:::button_close_modal()),
tags$div( update_factor_ui(id),
style = "display: none;", tags$div(
textInput(inputId = ns("hidden"), label = NULL, value = datamods:::genId()) style = "display: none;",
), textInput(
easyClose = easyClose, inputId = ns("hidden"),
size = size, label = NULL,
footer = footer value = datamods:::genId()
)) )
),
easyClose = easyClose,
size = size,
footer = footer
)
)
} }
@ -346,10 +333,11 @@ winbox_update_factor <- function(id,
title = title, title = title,
ui = tagList( ui = tagList(
update_factor_ui(id), update_factor_ui(id),
tags$div( tags$div(style = "display: none;", textInput(
style = "display: none;", inputId = ns("hidden"),
textInput(inputId = ns("hidden"), label = NULL, value = genId()) label = NULL,
) value = genId()
))
), ),
options = modifyList( options = modifyList(
shinyWidgets::wbOptions(height = "615px", modal = TRUE), shinyWidgets::wbOptions(height = "615px", modal = TRUE),

441
SESSION.md
View file

@ -1,21 +1,21 @@
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
-------------------------------- R environment --------------------------------- -------------------------------- R environment ---------------------------------
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
|setting |value | |setting |value |
|:-----------|:----------------------------------------------| |:-----------|:------------------------------------------|
|version |R version 4.4.1 (2024-06-14) | |version |R version 4.5.2 (2025-10-31) |
|os |macOS 26.1 | |os |macOS Tahoe 26.3 |
|system |aarch64, darwin20 | |system |aarch64, darwin20 |
|ui |RStudio | |ui |RStudio |
|language |(EN) | |language |(EN) |
|collate |en_US.UTF-8 | |collate |en_US.UTF-8 |
|ctype |en_US.UTF-8 | |ctype |en_US.UTF-8 |
|tz |Europe/Copenhagen | |tz |Europe/Copenhagen |
|date |2026-01-06 | |date |2026-02-23 |
|rstudio |2025.09.2+418 Cucumberleaf Sunflower (desktop) | |rstudio |2026.01.1+403 Apple Blossom (desktop) |
|pandoc |3.6.4 @ /opt/homebrew/bin/ (via rmarkdown) | |pandoc |3.6.4 @ /opt/homebrew/bin/ (via rmarkdown) |
|quarto |1.7.30 @ /usr/local/bin/quarto | |quarto |1.7.30 @ /usr/local/bin/quarto |
|FreesearchR |26.1.1.260106 | |FreesearchR |26.2.1.260223 |
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
@ -23,204 +23,213 @@
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
|package |loadedversion |date |source | |package |loadedversion |date |source |
|:-----------------|:-------------|:----------|:--------------| |:-----------------|:-------------|:----------|:--------------|
|apexcharter |0.4.4 |2024-09-06 |CRAN (R 4.4.1) | |apexcharter |0.4.5 |2026-01-07 |CRAN (R 4.5.2) |
|askpass |1.2.1 |2024-10-04 |CRAN (R 4.4.1) | |askpass |1.2.1 |2024-10-04 |CRAN (R 4.5.0) |
|assertthat |0.2.1 |2019-03-21 |CRAN (R 4.4.1) | |assertthat |0.2.1 |2019-03-21 |CRAN (R 4.5.0) |
|backports |1.5.0 |2024-05-23 |CRAN (R 4.4.1) | |attachment |0.4.5 |2025-03-14 |CRAN (R 4.5.0) |
|base64enc |0.1-3 |2015-07-28 |CRAN (R 4.4.1) | |attempt |0.3.1 |2020-05-03 |CRAN (R 4.5.0) |
|bayestestR |0.17.0 |2025-08-29 |CRAN (R 4.4.1) | |backports |1.5.0 |2024-05-23 |CRAN (R 4.5.0) |
|bit |4.6.0 |2025-03-06 |CRAN (R 4.4.1) | |base64enc |0.1-6 |2026-02-02 |CRAN (R 4.5.2) |
|bit64 |4.6.0-1 |2025-01-16 |CRAN (R 4.4.1) | |bayestestR |0.17.0 |2025-08-29 |CRAN (R 4.5.0) |
|bitops |1.0-9 |2024-10-03 |CRAN (R 4.4.1) | |bit |4.6.0 |2025-03-06 |CRAN (R 4.5.0) |
|boot |1.3-32 |2025-08-29 |CRAN (R 4.4.1) | |bit64 |4.6.0-1 |2025-01-16 |CRAN (R 4.5.0) |
|brio |1.1.5 |2024-04-24 |CRAN (R 4.4.1) | |bitops |1.0-9 |2024-10-03 |CRAN (R 4.5.0) |
|broom |1.0.11 |2025-12-04 |CRAN (R 4.4.3) | |boot |1.3-32 |2025-08-29 |CRAN (R 4.5.2) |
|broom.helpers |1.22.0 |2025-09-17 |CRAN (R 4.4.1) | |brio |1.1.5 |2024-04-24 |CRAN (R 4.5.0) |
|bsicons |0.1.2 |2023-11-04 |CRAN (R 4.4.0) | |broom |1.0.12 |2026-01-27 |CRAN (R 4.5.2) |
|bslib |0.9.0 |2025-01-30 |CRAN (R 4.4.1) | |broom.helpers |1.22.0 |2025-09-17 |CRAN (R 4.5.0) |
|cachem |1.1.0 |2024-05-16 |CRAN (R 4.4.1) | |bsicons |0.1.2 |2023-11-04 |CRAN (R 4.5.0) |
|calendar |0.2.0 |2024-08-20 |CRAN (R 4.4.1) | |bslib |0.10.0 |2026-01-26 |CRAN (R 4.5.2) |
|cards |0.7.1 |2025-12-02 |CRAN (R 4.4.3) | |cachem |1.1.0 |2024-05-16 |CRAN (R 4.5.0) |
|cardx |0.3.1 |2025-12-04 |CRAN (R 4.4.3) | |calendar |0.2.0 |2024-08-20 |CRAN (R 4.5.0) |
|caTools |1.18.3 |2024-09-04 |CRAN (R 4.4.1) | |cards |0.7.1 |2025-12-02 |CRAN (R 4.5.2) |
|cellranger |1.1.0 |2016-07-27 |CRAN (R 4.4.0) | |cardx |0.3.2 |2026-02-05 |CRAN (R 4.5.2) |
|checkmate |2.3.3 |2025-08-18 |CRAN (R 4.4.1) | |caTools |1.18.3 |2024-09-04 |CRAN (R 4.5.0) |
|class |7.3-23 |2025-01-01 |CRAN (R 4.4.1) | |cellranger |1.1.0 |2016-07-27 |CRAN (R 4.5.0) |
|classInt |0.4-11 |2025-01-08 |CRAN (R 4.4.1) | |checkmate |2.3.4 |2026-02-03 |CRAN (R 4.5.2) |
|cli |3.6.5 |2025-04-23 |CRAN (R 4.4.1) | |class |7.3-23 |2025-01-01 |CRAN (R 4.5.2) |
|cluster |2.1.8.1 |2025-03-12 |CRAN (R 4.4.1) | |classInt |0.4-11 |2025-01-08 |CRAN (R 4.5.0) |
|codetools |0.2-20 |2024-03-31 |CRAN (R 4.4.1) | |cli |3.6.5 |2025-04-23 |CRAN (R 4.5.0) |
|colorspace |2.1-2 |2025-09-22 |CRAN (R 4.4.1) | |cluster |2.1.8.2 |2026-02-05 |CRAN (R 4.5.2) |
|commonmark |2.0.0 |2025-07-07 |CRAN (R 4.4.1) | |codetools |0.2-20 |2024-03-31 |CRAN (R 4.5.2) |
|crayon |1.5.3 |2024-06-20 |CRAN (R 4.4.1) | |colorspace |2.1-2 |2025-09-22 |CRAN (R 4.5.0) |
|data.table |1.17.8 |2025-07-10 |CRAN (R 4.4.1) | |commonmark |2.0.0 |2025-07-07 |CRAN (R 4.5.0) |
|datamods |1.5.3 |2024-10-02 |CRAN (R 4.4.1) | |crayon |1.5.3 |2024-06-20 |CRAN (R 4.5.0) |
|datawizard |1.3.0 |2025-10-11 |CRAN (R 4.4.1) | |data.table |1.18.2.1 |2026-01-27 |CRAN (R 4.5.2) |
|DEoptimR |1.1-4 |2025-07-27 |CRAN (R 4.4.1) | |datamods |1.5.3 |2024-10-02 |CRAN (R 4.5.0) |
|desc |1.4.3 |2023-12-10 |CRAN (R 4.4.1) | |datawizard |1.3.0 |2025-10-11 |CRAN (R 4.5.0) |
|devtools |2.4.6 |2025-10-03 |CRAN (R 4.4.1) | |DEoptimR |1.1-4 |2025-07-27 |CRAN (R 4.5.0) |
|DHARMa |0.4.7 |2024-10-18 |CRAN (R 4.4.1) | |desc |1.4.3 |2023-12-10 |CRAN (R 4.5.0) |
|digest |0.6.39 |2025-11-19 |CRAN (R 4.4.3) | |devtools |2.4.6 |2025-10-03 |CRAN (R 4.5.0) |
|doParallel |1.0.17 |2022-02-07 |CRAN (R 4.4.0) | |DHARMa |0.4.7 |2024-10-18 |CRAN (R 4.5.0) |
|dplyr |1.1.4 |2023-11-17 |CRAN (R 4.4.0) | |digest |0.6.39 |2025-11-19 |CRAN (R 4.5.2) |
|DT |0.34.0 |2025-09-02 |CRAN (R 4.4.1) | |dockerfiler |0.2.5 |2025-05-07 |CRAN (R 4.5.0) |
|e1071 |1.7-16 |2024-09-16 |CRAN (R 4.4.1) | |doParallel |1.0.17 |2022-02-07 |CRAN (R 4.5.0) |
|easystats |0.7.5 |2025-07-11 |CRAN (R 4.4.1) | |dplyr |1.2.0 |2026-02-03 |CRAN (R 4.5.2) |
|ellipsis |0.3.2 |2021-04-29 |CRAN (R 4.4.1) | |DT |0.34.0 |2025-09-02 |CRAN (R 4.5.0) |
|emmeans |2.0.0 |2025-10-29 |CRAN (R 4.4.1) | |e1071 |1.7-17 |2025-12-18 |CRAN (R 4.5.2) |
|esquisse |2.1.0 |2025-02-21 |CRAN (R 4.4.1) | |easystats |0.7.5 |2025-07-11 |CRAN (R 4.5.0) |
|estimability |1.5.1 |2024-05-12 |CRAN (R 4.4.1) | |ellipsis |0.3.2 |2021-04-29 |CRAN (R 4.5.0) |
|eulerr |7.0.4 |2025-09-24 |CRAN (R 4.4.1) | |emmeans |2.0.1 |2025-12-16 |CRAN (R 4.5.2) |
|evaluate |1.0.5 |2025-08-27 |CRAN (R 4.4.1) | |esquisse |2.1.0 |2025-02-21 |CRAN (R 4.5.0) |
|farver |2.1.2 |2024-05-13 |CRAN (R 4.4.1) | |estimability |1.5.1 |2024-05-12 |CRAN (R 4.5.0) |
|fastmap |1.2.0 |2024-05-15 |CRAN (R 4.4.1) | |eulerr |7.0.4 |2025-09-24 |CRAN (R 4.5.0) |
|flextable |0.9.10 |2025-08-24 |CRAN (R 4.4.1) | |evaluate |1.0.5 |2025-08-27 |CRAN (R 4.5.0) |
|fontawesome |0.5.3 |2024-11-16 |CRAN (R 4.4.1) | |farver |2.1.2 |2024-05-13 |CRAN (R 4.5.0) |
|fontBitstreamVera |0.1.1 |2017-02-01 |CRAN (R 4.4.1) | |fastmap |1.2.0 |2024-05-15 |CRAN (R 4.5.0) |
|fontLiberation |0.1.0 |2016-10-15 |CRAN (R 4.4.1) | |flextable |0.9.11 |2026-02-13 |CRAN (R 4.5.2) |
|fontquiver |0.2.1 |2017-02-01 |CRAN (R 4.4.0) | |fontawesome |0.5.3 |2024-11-16 |CRAN (R 4.5.0) |
|forcats |1.0.1 |2025-09-25 |CRAN (R 4.4.1) | |fontBitstreamVera |0.1.1 |2017-02-01 |CRAN (R 4.5.0) |
|foreach |1.5.2 |2022-02-02 |CRAN (R 4.4.0) | |fontLiberation |0.1.0 |2016-10-15 |CRAN (R 4.5.0) |
|foreign |0.8-90 |2025-03-31 |CRAN (R 4.4.1) | |fontquiver |0.2.1 |2017-02-01 |CRAN (R 4.5.0) |
|Formula |1.2-5 |2023-02-24 |CRAN (R 4.4.1) | |forcats |1.0.1 |2025-09-25 |CRAN (R 4.5.0) |
|FreesearchR |26.1.1 |NA |NA | |foreach |1.5.2 |2022-02-02 |CRAN (R 4.5.0) |
|fs |1.6.6 |2025-04-12 |CRAN (R 4.4.1) | |foreign |0.8-90 |2025-03-31 |CRAN (R 4.5.2) |
|gdtools |0.4.4 |2025-10-06 |CRAN (R 4.4.1) | |Formula |1.2-5 |2023-02-24 |CRAN (R 4.5.0) |
|generics |0.1.4 |2025-05-09 |CRAN (R 4.4.1) | |FreesearchR |26.2.1 |NA |NA |
|ggalluvial |0.12.5 |2023-02-22 |CRAN (R 4.4.0) | |fs |1.6.6 |2025-04-12 |CRAN (R 4.5.0) |
|ggcorrplot |0.1.4.1 |2023-09-05 |CRAN (R 4.4.0) | |gdtools |0.5.0 |2026-02-09 |CRAN (R 4.5.2) |
|ggforce |0.5.0 |2025-06-18 |CRAN (R 4.4.1) | |generics |0.1.4 |2025-05-09 |CRAN (R 4.5.0) |
|ggplot2 |4.0.1 |2025-11-14 |CRAN (R 4.4.1) | |ggalluvial |0.12.5 |2023-02-22 |CRAN (R 4.5.0) |
|ggridges |0.5.7 |2025-08-27 |CRAN (R 4.4.1) | |ggcorrplot |0.1.4.1 |2023-09-05 |CRAN (R 4.5.0) |
|ggstats |0.11.0 |2025-09-15 |CRAN (R 4.4.1) | |ggforce |0.5.0 |2025-06-18 |CRAN (R 4.5.0) |
|glue |1.8.0 |2024-09-30 |CRAN (R 4.4.1) | |ggplot2 |4.0.2 |2026-02-03 |CRAN (R 4.5.2) |
|gridExtra |2.3 |2017-09-09 |CRAN (R 4.4.1) | |ggridges |0.5.7 |2025-08-27 |CRAN (R 4.5.0) |
|gt |1.1.0 |2025-09-23 |CRAN (R 4.4.1) | |ggstats |0.12.0 |2025-12-22 |CRAN (R 4.5.2) |
|gtable |0.3.6 |2024-10-25 |CRAN (R 4.4.1) | |glue |1.8.0 |2024-09-30 |CRAN (R 4.5.0) |
|gtsummary |2.5.0 |2025-12-05 |CRAN (R 4.4.3) | |gridExtra |2.3 |2017-09-09 |CRAN (R 4.5.0) |
|haven |2.5.5 |2025-05-30 |CRAN (R 4.4.1) | |gt |1.3.0 |2026-01-22 |CRAN (R 4.5.2) |
|here |1.0.2 |2025-09-15 |CRAN (R 4.4.1) | |gtable |0.3.6 |2024-10-25 |CRAN (R 4.5.0) |
|Hmisc |5.2-4 |2025-10-05 |CRAN (R 4.4.1) | |gtsummary |2.5.0 |2025-12-05 |CRAN (R 4.5.2) |
|hms |1.1.4 |2025-10-17 |CRAN (R 4.4.1) | |haven |2.5.5 |2025-05-30 |CRAN (R 4.5.0) |
|htmlTable |2.4.3 |2024-07-21 |CRAN (R 4.4.0) | |here |1.0.2 |2025-09-15 |CRAN (R 4.5.0) |
|htmltools |0.5.9 |2025-12-04 |CRAN (R 4.4.3) | |Hmisc |5.2-5 |2026-01-09 |CRAN (R 4.5.2) |
|htmlwidgets |1.6.4 |2023-12-06 |CRAN (R 4.4.0) | |hms |1.1.4 |2025-10-17 |CRAN (R 4.5.0) |
|httpuv |1.6.16 |2025-04-16 |CRAN (R 4.4.1) | |htmlTable |2.4.3 |2024-07-21 |CRAN (R 4.5.0) |
|IDEAFilter |0.2.1 |2025-07-29 |CRAN (R 4.4.1) | |htmltools |0.5.9 |2025-12-04 |CRAN (R 4.5.2) |
|insight |1.4.4 |2025-12-06 |CRAN (R 4.4.3) | |htmlwidgets |1.6.4 |2023-12-06 |CRAN (R 4.5.0) |
|iterators |1.0.14 |2022-02-05 |CRAN (R 4.4.1) | |httpuv |1.6.16 |2025-04-16 |CRAN (R 4.5.0) |
|jquerylib |0.1.4 |2021-04-26 |CRAN (R 4.4.0) | |IDEAFilter |0.2.1 |2025-07-29 |CRAN (R 4.5.0) |
|jsonlite |2.0.0 |2025-03-27 |CRAN (R 4.4.1) | |insight |1.4.6 |2026-02-04 |CRAN (R 4.5.2) |
|KernSmooth |2.23-26 |2025-01-01 |CRAN (R 4.4.1) | |iterators |1.0.14 |2022-02-05 |CRAN (R 4.5.0) |
|keyring |1.4.1 |2025-06-15 |CRAN (R 4.4.1) | |jquerylib |0.1.4 |2021-04-26 |CRAN (R 4.5.0) |
|knitr |1.50 |2025-03-16 |CRAN (R 4.4.1) | |jsonlite |2.0.0 |2025-03-27 |CRAN (R 4.5.0) |
|later |1.4.4 |2025-08-27 |CRAN (R 4.4.1) | |KernSmooth |2.23-26 |2025-01-01 |CRAN (R 4.5.2) |
|lattice |0.22-7 |2025-04-02 |CRAN (R 4.4.1) | |keyring |1.4.1 |2025-06-15 |CRAN (R 4.5.0) |
|lifecycle |1.0.4 |2023-11-07 |CRAN (R 4.4.1) | |knitr |1.51 |2025-12-20 |CRAN (R 4.5.2) |
|lme4 |1.1-38 |2025-12-02 |CRAN (R 4.4.3) | |labeling |0.4.3 |2023-08-29 |CRAN (R 4.5.0) |
|lubridate |1.9.4 |2024-12-08 |CRAN (R 4.4.1) | |later |1.4.6 |2026-02-13 |CRAN (R 4.5.2) |
|magrittr |2.0.4 |2025-09-12 |CRAN (R 4.4.1) | |lattice |0.22-7 |2025-04-02 |CRAN (R 4.5.2) |
|MASS |7.3-65 |2025-02-28 |CRAN (R 4.4.1) | |lifecycle |1.0.5 |2026-01-08 |CRAN (R 4.5.2) |
|Matrix |1.7-4 |2025-08-28 |CRAN (R 4.4.1) | |litedown |0.9 |2025-12-18 |CRAN (R 4.5.2) |
|memoise |2.0.1 |2021-11-26 |CRAN (R 4.4.0) | |lme4 |1.1-38 |2025-12-02 |CRAN (R 4.5.2) |
|mime |0.13 |2025-03-17 |CRAN (R 4.4.1) | |lubridate |1.9.5 |2026-02-04 |CRAN (R 4.5.2) |
|minqa |1.2.8 |2024-08-17 |CRAN (R 4.4.1) | |magrittr |2.0.4 |2025-09-12 |CRAN (R 4.5.0) |
|mvtnorm |1.3-3 |2025-01-10 |CRAN (R 4.4.1) | |markdown |2.0 |2025-03-23 |CRAN (R 4.5.0) |
|NHANES |2.1.0 |2015-07-02 |CRAN (R 4.4.0) | |MASS |7.3-65 |2025-02-28 |CRAN (R 4.5.0) |
|nlme |3.1-168 |2025-03-31 |CRAN (R 4.4.1) | |Matrix |1.7-4 |2025-08-28 |CRAN (R 4.5.2) |
|nloptr |2.2.1 |2025-03-17 |CRAN (R 4.4.1) | |memoise |2.0.1 |2021-11-26 |CRAN (R 4.5.0) |
|nnet |7.3-20 |2025-01-01 |CRAN (R 4.4.1) | |mime |0.13 |2025-03-17 |CRAN (R 4.5.0) |
|officer |0.7.2 |2025-12-04 |CRAN (R 4.4.3) | |minqa |1.2.8 |2024-08-17 |CRAN (R 4.5.0) |
|opdisDownsampling |1.0.1 |2024-04-15 |CRAN (R 4.4.0) | |mvtnorm |1.3-3 |2025-01-10 |CRAN (R 4.5.0) |
|openssl |2.3.4 |2025-09-30 |CRAN (R 4.4.1) | |NHANES |2.1.0 |2015-07-02 |CRAN (R 4.5.0) |
|openxlsx2 |1.22 |2025-12-07 |CRAN (R 4.4.3) | |nlme |3.1-168 |2025-03-31 |CRAN (R 4.5.2) |
|otel |0.2.0 |2025-08-29 |CRAN (R 4.4.1) | |nloptr |2.2.1 |2025-03-17 |CRAN (R 4.5.0) |
|parameters |0.28.3 |2025-11-25 |CRAN (R 4.4.3) | |nnet |7.3-20 |2025-01-01 |CRAN (R 4.5.2) |
|patchwork |1.3.2 |2025-08-25 |CRAN (R 4.4.1) | |officer |0.7.3 |2026-01-16 |CRAN (R 4.5.2) |
|pbmcapply |1.5.1 |2022-04-28 |CRAN (R 4.4.1) | |opdisDownsampling |1.0.1 |2024-04-15 |CRAN (R 4.5.0) |
|performance |0.15.3 |2025-12-01 |CRAN (R 4.4.3) | |openssl |2.3.4 |2025-09-30 |CRAN (R 4.5.0) |
|phosphoricons |0.2.1 |2024-04-08 |CRAN (R 4.4.0) | |openxlsx2 |1.23.1 |2026-01-19 |CRAN (R 4.5.2) |
|pillar |1.11.1 |2025-09-17 |CRAN (R 4.4.1) | |otel |0.2.0 |2025-08-29 |CRAN (R 4.5.0) |
|pkgbuild |1.4.8 |2025-05-26 |CRAN (R 4.4.1) | |pak |0.9.2 |2025-12-22 |CRAN (R 4.5.2) |
|pkgconfig |2.0.3 |2019-09-22 |CRAN (R 4.4.1) | |parameters |0.28.3 |2025-11-25 |CRAN (R 4.5.2) |
|pkgload |1.4.1 |2025-09-23 |CRAN (R 4.4.1) | |patchwork |1.3.2 |2025-08-25 |CRAN (R 4.5.0) |
|plyr |1.8.9 |2023-10-02 |CRAN (R 4.4.1) | |pbmcapply |1.5.1 |2022-04-28 |CRAN (R 4.5.0) |
|polyclip |1.10-7 |2024-07-23 |CRAN (R 4.4.1) | |performance |0.16.0 |2026-02-04 |CRAN (R 4.5.2) |
|pracma |2.4.6 |2025-10-22 |CRAN (R 4.4.1) | |phosphoricons |0.2.1 |2024-04-08 |CRAN (R 4.5.0) |
|processx |3.8.6 |2025-02-21 |CRAN (R 4.4.1) | |pillar |1.11.1 |2025-09-17 |CRAN (R 4.5.0) |
|promises |1.5.0 |2025-11-01 |CRAN (R 4.4.1) | |pkgbuild |1.4.8 |2025-05-26 |CRAN (R 4.5.0) |
|proxy |0.4-27 |2022-06-09 |CRAN (R 4.4.1) | |pkgconfig |2.0.3 |2019-09-22 |CRAN (R 4.5.0) |
|ps |1.9.1 |2025-04-12 |CRAN (R 4.4.1) | |pkgload |1.5.0 |2026-02-03 |CRAN (R 4.5.2) |
|purrr |1.2.0 |2025-11-04 |CRAN (R 4.4.1) | |plyr |1.8.9 |2023-10-02 |CRAN (R 4.5.0) |
|qqconf |1.3.2 |2023-04-14 |CRAN (R 4.4.0) | |polyclip |1.10-7 |2024-07-23 |CRAN (R 4.5.0) |
|qqplotr |0.0.7 |2025-09-05 |CRAN (R 4.4.1) | |pracma |2.4.6 |2025-10-22 |CRAN (R 4.5.0) |
|quarto |1.5.1 |2025-09-04 |CRAN (R 4.4.1) | |processx |3.8.6 |2025-02-21 |CRAN (R 4.5.0) |
|R6 |2.6.1 |2025-02-15 |CRAN (R 4.4.1) | |promises |1.5.0 |2025-11-01 |CRAN (R 4.5.0) |
|ragg |1.5.0 |2025-09-02 |CRAN (R 4.4.1) | |proxy |0.4-29 |2025-12-29 |CRAN (R 4.5.2) |
|rankinPlot |1.1.0 |2023-01-30 |CRAN (R 4.4.0) | |ps |1.9.1 |2025-04-12 |CRAN (R 4.5.0) |
|rbibutils |2.4 |2025-11-07 |CRAN (R 4.4.1) | |purrr |1.2.1 |2026-01-09 |CRAN (R 4.5.2) |
|RColorBrewer |1.1-3 |2022-04-03 |CRAN (R 4.4.1) | |qqconf |1.3.2 |2023-04-14 |CRAN (R 4.5.0) |
|Rcpp |1.1.0 |2025-07-02 |CRAN (R 4.4.1) | |qqplotr |0.0.7 |2025-09-05 |CRAN (R 4.5.0) |
|RcppArmadillo |15.2.2-1 |2025-11-22 |CRAN (R 4.4.3) | |quarto |1.5.1 |2025-09-04 |CRAN (R 4.5.0) |
|Rdpack |2.6.4 |2025-04-09 |CRAN (R 4.4.1) | |R6 |2.6.1 |2025-02-15 |CRAN (R 4.5.0) |
|reactable |0.4.5 |2025-12-01 |CRAN (R 4.4.3) | |ragg |1.5.0 |2025-09-02 |CRAN (R 4.5.0) |
|readODS |2.3.2 |2025-01-13 |CRAN (R 4.4.1) | |rankinPlot |1.1.0 |2023-01-30 |CRAN (R 4.5.0) |
|readr |2.1.6 |2025-11-14 |CRAN (R 4.4.3) | |rbibutils |2.4.1 |2026-01-21 |CRAN (R 4.5.2) |
|readxl |1.4.5 |2025-03-07 |CRAN (R 4.4.1) | |RColorBrewer |1.1-3 |2022-04-03 |CRAN (R 4.5.0) |
|REDCapCAST |25.3.2 |2025-03-10 |CRAN (R 4.4.1) | |Rcpp |1.1.1 |2026-01-10 |CRAN (R 4.5.2) |
|REDCapR |1.6.0 |2025-10-08 |CRAN (R 4.4.1) | |RcppArmadillo |15.2.3-1 |2025-12-17 |CRAN (R 4.5.2) |
|reformulas |0.4.2 |2025-10-28 |CRAN (R 4.4.1) | |Rdpack |2.6.6 |2026-02-08 |CRAN (R 4.5.2) |
|remotes |2.5.0 |2024-03-17 |CRAN (R 4.4.1) | |reactable |0.4.5 |2025-12-01 |CRAN (R 4.5.2) |
|rempsyc |0.2.0 |2025-09-15 |CRAN (R 4.4.1) | |readODS |2.3.2 |2025-01-13 |CRAN (R 4.5.0) |
|renv |1.1.5 |2025-07-24 |CRAN (R 4.4.1) | |readr |2.2.0 |2026-02-19 |CRAN (R 4.5.2) |
|reshape2 |1.4.5 |2025-11-12 |CRAN (R 4.4.1) | |readxl |1.4.5 |2025-03-07 |CRAN (R 4.5.0) |
|rio |1.2.4 |2025-09-26 |CRAN (R 4.4.1) | |REDCapCAST |26.1.1 |2026-01-29 |CRAN (R 4.5.2) |
|rlang |1.1.6 |2025-04-11 |CRAN (R 4.4.1) | |REDCapR |1.6.0 |2025-10-08 |CRAN (R 4.5.0) |
|rmarkdown |2.30 |2025-09-28 |CRAN (R 4.4.1) | |reformulas |0.4.4 |2026-02-02 |CRAN (R 4.5.2) |
|robustbase |0.99-6 |2025-09-04 |CRAN (R 4.4.1) | |remotes |2.5.0 |2024-03-17 |CRAN (R 4.5.0) |
|roxygen2 |7.3.3 |2025-09-03 |CRAN (R 4.4.1) | |rempsyc |0.2.0 |2025-09-15 |CRAN (R 4.5.0) |
|rpart |4.1.24 |2025-01-07 |CRAN (R 4.4.1) | |renv |1.1.7 |2026-01-27 |CRAN (R 4.5.2) |
|rprojroot |2.1.1 |2025-08-26 |CRAN (R 4.4.1) | |reshape2 |1.4.5 |2025-11-12 |CRAN (R 4.5.0) |
|rsconnect |1.7.0 |2025-12-06 |CRAN (R 4.4.3) | |rio |1.2.4 |2025-09-26 |CRAN (R 4.5.0) |
|rstudioapi |0.17.1 |2024-10-22 |CRAN (R 4.4.1) | |rlang |1.1.7 |2026-01-09 |CRAN (R 4.5.2) |
|S7 |0.2.1 |2025-11-14 |CRAN (R 4.4.3) | |rmarkdown |2.30 |2025-09-28 |CRAN (R 4.5.0) |
|sass |0.4.10 |2025-04-11 |CRAN (R 4.4.1) | |robustbase |0.99-7 |2026-02-05 |CRAN (R 4.5.2) |
|scales |1.4.0 |2025-04-24 |CRAN (R 4.4.1) | |roxygen2 |7.3.3 |2025-09-03 |CRAN (R 4.5.0) |
|see |0.12.0 |2025-09-14 |CRAN (R 4.4.1) | |rpart |4.1.24 |2025-01-07 |CRAN (R 4.5.2) |
|sessioninfo |1.2.3 |2025-02-05 |CRAN (R 4.4.1) | |rprojroot |2.1.1 |2025-08-26 |CRAN (R 4.5.0) |
|shiny |1.12.1 |2025-12-09 |CRAN (R 4.4.1) | |rsconnect |1.7.0 |2025-12-06 |CRAN (R 4.5.2) |
|shiny.i18n |0.3.0 |2023-01-16 |CRAN (R 4.4.0) | |rstudioapi |0.18.0 |2026-01-16 |CRAN (R 4.5.2) |
|shinybusy |0.3.3 |2024-03-09 |CRAN (R 4.4.0) | |S7 |0.2.1 |2025-11-14 |CRAN (R 4.5.2) |
|shinyjs |2.1.0 |2021-12-23 |CRAN (R 4.4.0) | |sass |0.4.10 |2025-04-11 |CRAN (R 4.5.0) |
|shinyTime |1.0.3 |2022-08-19 |CRAN (R 4.4.0) | |scales |1.4.0 |2025-04-24 |CRAN (R 4.5.0) |
|shinyWidgets |0.9.0 |2025-02-21 |CRAN (R 4.4.1) | |see |0.13.0 |2026-01-30 |CRAN (R 4.5.2) |
|smd |0.8.0 |2025-02-12 |CRAN (R 4.4.1) | |sessioninfo |1.2.3 |2025-02-05 |CRAN (R 4.5.0) |
|stringi |1.8.7 |2025-03-27 |CRAN (R 4.4.1) | |shiny |1.13.0 |2026-02-20 |CRAN (R 4.5.2) |
|stringr |1.6.0 |2025-11-04 |CRAN (R 4.4.1) | |shiny.i18n |0.3.0 |2023-01-16 |CRAN (R 4.5.0) |
|stRoke |25.9.2 |2025-09-30 |CRAN (R 4.4.1) | |shiny2docker |0.0.3 |2025-06-28 |CRAN (R 4.5.0) |
|systemfonts |1.3.1 |2025-10-01 |CRAN (R 4.4.1) | |shinybusy |0.3.3 |2024-03-09 |CRAN (R 4.5.0) |
|testthat |3.3.1 |2025-11-25 |CRAN (R 4.4.3) | |shinyjs |2.1.1 |2026-01-15 |CRAN (R 4.5.2) |
|textshaping |1.0.4 |2025-10-10 |CRAN (R 4.4.1) | |shinyTime |1.0.3 |2022-08-19 |CRAN (R 4.5.0) |
|thematic |0.1.8 |2025-09-29 |CRAN (R 4.4.1) | |shinyWidgets |0.9.0 |2025-02-21 |CRAN (R 4.5.0) |
|tibble |3.3.0 |2025-06-08 |CRAN (R 4.4.1) | |smd |0.8.0 |2025-02-12 |CRAN (R 4.5.0) |
|tidyr |1.3.1 |2024-01-24 |CRAN (R 4.4.1) | |stringi |1.8.7 |2025-03-27 |CRAN (R 4.5.0) |
|tidyselect |1.2.1 |2024-03-11 |CRAN (R 4.4.0) | |stringr |1.6.0 |2025-11-04 |CRAN (R 4.5.0) |
|timechange |0.3.0 |2024-01-18 |CRAN (R 4.4.1) | |stRoke |25.9.2 |2025-09-30 |CRAN (R 4.5.0) |
|toastui |0.4.0 |2025-04-03 |CRAN (R 4.4.1) | |systemfonts |1.3.1 |2025-10-01 |CRAN (R 4.5.0) |
|tweenr |2.0.3 |2024-02-26 |CRAN (R 4.4.0) | |testthat |3.3.2 |2026-01-11 |CRAN (R 4.5.2) |
|twosamples |2.0.1 |2023-06-23 |CRAN (R 4.4.1) | |textshaping |1.0.4 |2025-10-10 |CRAN (R 4.5.0) |
|tzdb |0.5.0 |2025-03-15 |CRAN (R 4.4.1) | |thematic |0.1.8 |2025-09-29 |CRAN (R 4.5.0) |
|usethis |3.2.1 |2025-09-06 |CRAN (R 4.4.1) | |tibble |3.3.1 |2026-01-11 |CRAN (R 4.5.2) |
|utf8 |1.2.6 |2025-06-08 |CRAN (R 4.4.1) | |tidyr |1.3.2 |2025-12-19 |CRAN (R 4.5.2) |
|uuid |1.2-1 |2024-07-29 |CRAN (R 4.4.1) | |tidyselect |1.2.1 |2024-03-11 |CRAN (R 4.5.0) |
|vctrs |0.6.5 |2023-12-01 |CRAN (R 4.4.0) | |timechange |0.4.0 |2026-01-29 |CRAN (R 4.5.2) |
|viridis |0.6.5 |2024-01-29 |CRAN (R 4.4.0) | |toastui |0.4.0 |2025-04-03 |CRAN (R 4.5.0) |
|viridisLite |0.4.2 |2023-05-02 |CRAN (R 4.4.1) | |tweenr |2.0.3 |2024-02-26 |CRAN (R 4.5.0) |
|vroom |1.6.7 |2025-11-28 |CRAN (R 4.4.3) | |twosamples |2.0.1 |2023-06-23 |CRAN (R 4.5.0) |
|withr |3.0.2 |2024-10-28 |CRAN (R 4.4.1) | |tzdb |0.5.0 |2025-03-15 |CRAN (R 4.5.0) |
|writexl |1.5.4 |2025-04-15 |CRAN (R 4.4.1) | |usethis |3.2.1 |2025-09-06 |CRAN (R 4.5.0) |
|xfun |0.54 |2025-10-30 |CRAN (R 4.4.1) | |utf8 |1.2.6 |2025-06-08 |CRAN (R 4.5.0) |
|xml2 |1.5.1 |2025-12-01 |CRAN (R 4.4.3) | |uuid |1.2-2 |2026-01-23 |CRAN (R 4.5.2) |
|xtable |1.8-4 |2019-04-21 |CRAN (R 4.4.1) | |vctrs |0.7.1 |2026-01-23 |CRAN (R 4.5.2) |
|yaml |2.3.11 |2025-11-28 |CRAN (R 4.4.3) | |viridis |0.6.5 |2024-01-29 |CRAN (R 4.5.0) |
|zip |2.3.3 |2025-05-13 |CRAN (R 4.4.1) | |viridisLite |0.4.3 |2026-02-04 |CRAN (R 4.5.2) |
|vroom |1.7.0 |2026-01-27 |CRAN (R 4.5.2) |
|withr |3.0.2 |2024-10-28 |CRAN (R 4.5.0) |
|writexl |1.5.4 |2025-04-15 |CRAN (R 4.5.0) |
|xfun |0.56 |2026-01-18 |CRAN (R 4.5.2) |
|xml2 |1.5.2 |2026-01-17 |CRAN (R 4.5.2) |
|xtable |1.8-4 |2019-04-21 |CRAN (R 4.5.0) |
|yaml |2.3.12 |2025-12-10 |CRAN (R 4.5.2) |
|yesno |0.1.3 |2024-07-26 |CRAN (R 4.5.0) |
|zip |2.3.3 |2025-05-13 |CRAN (R 4.5.0) |

4
app_docker/Dockerfile
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@ -1,9 +1,9 @@
FROM rocker/tidyverse:4.4.1 FROM rocker/tidyverse:4.5.2
RUN apt-get update -y && apt-get install -y cmake make libcurl4-openssl-dev libicu-dev libssl-dev pandoc zlib1g-dev libsecret-1-dev libxml2-dev libx11-dev libcairo2-dev libfontconfig1-dev libfreetype6-dev libfribidi-dev libharfbuzz-dev libjpeg-dev libpng-dev libtiff-dev libwebp-dev libfftw3-dev && rm -rf /var/lib/apt/lists/* RUN apt-get update -y && apt-get install -y cmake make libcurl4-openssl-dev libicu-dev libssl-dev pandoc zlib1g-dev libsecret-1-dev libxml2-dev libx11-dev libcairo2-dev libfontconfig1-dev libfreetype6-dev libfribidi-dev libharfbuzz-dev libjpeg-dev libpng-dev libtiff-dev libwebp-dev libfftw3-dev && rm -rf /var/lib/apt/lists/*
RUN mkdir -p /usr/local/lib/R/etc/ /usr/lib/R/etc/ RUN mkdir -p /usr/local/lib/R/etc/ /usr/lib/R/etc/
RUN echo "options(renv.config.pak.enabled = FALSE, repos = c(CRAN = 'https://cran.rstudio.com/'), download.file.method = 'libcurl', Ncpus = 4)" | tee /usr/local/lib/R/etc/Rprofile.site | tee /usr/lib/R/etc/Rprofile.site RUN echo "options(renv.config.pak.enabled = FALSE, repos = c(CRAN = 'https://cran.rstudio.com/'), download.file.method = 'libcurl', Ncpus = 4)" | tee /usr/local/lib/R/etc/Rprofile.site | tee /usr/lib/R/etc/Rprofile.site
RUN R -e 'install.packages("remotes")' RUN R -e 'install.packages("remotes")'
RUN R -e 'remotes::install_version("renv", version = "1.1.5")' RUN R -e 'remotes::install_version("renv", version = "1.1.7")'
COPY renv.lock renv.lock COPY renv.lock renv.lock
RUN --mount=type=cache,id=renv-cache,target=/root/.cache/R/renv R -e 'renv::restore()' RUN --mount=type=cache,id=renv-cache,target=/root/.cache/R/renv R -e 'renv::restore()'
WORKDIR /srv/shiny-server/ WORKDIR /srv/shiny-server/

2210
app_docker/app.R
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540
app_docker/renv.lock
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36
app_docker/translations/translation_da.csv
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@ -5,7 +5,6 @@
"REDCap server export","Eksport fra REDCap server" "REDCap server export","Eksport fra REDCap server"
"Local or sample data","Lokal eller testdata" "Local or sample data","Lokal eller testdata"
"Please be mindfull handling sensitive data","Pas godt på og overvej nøje hvordan du håndterer personfølsomme data" "Please be mindfull handling sensitive data","Pas godt på og overvej nøje hvordan du håndterer personfølsomme data"
"The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).","***FreesearchR*** opbevarer alene data i forbindelse med din analyse, men du bør kun behandle personfølsomme data når du kører ***FreesearchR*** direkte på din egen maskine. [Læs mere her](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine)."
"Quick overview","Hurtigt overblik" "Quick overview","Hurtigt overblik"
"Select variables for final import","Vælg variabler til den endelige import" "Select variables for final import","Vælg variabler til den endelige import"
"Exclude incomplete variables:","Ekskluder inkomplette variabler:" "Exclude incomplete variables:","Ekskluder inkomplette variabler:"
@ -24,16 +23,11 @@
"Apply filter on observation","Anvend filtre af observationer" "Apply filter on observation","Anvend filtre af observationer"
"Edit and create data","Ændr og opret variabler" "Edit and create data","Ændr og opret variabler"
"Subset, rename and convert variables","Udvælg, omdøb og konverter variabler" "Subset, rename and convert variables","Udvælg, omdøb og konverter variabler"
"Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.).","Nedenfor er der mulighed for at lave simple ændringer i dit datasæt, såsom at redigere variabelnavne eller beskrivelser (bedre tabeller), eller omklassificering af variabler (numerisk, factoriel/kategorisk)."
"Please note that data modifications are applied before any filtering.","Bemærk at alle ændringer i data anvendes inden filtreringen."
"Advanced data manipulation","Avanceret datamanipulation" "Advanced data manipulation","Avanceret datamanipulation"
"Below options allow more advanced varaible manipulations.","Nedenfor er mulighed for avancerede ændringer i data." "Below options allow more advanced varaible manipulations.","Nedenfor er mulighed for avancerede ændringer i data."
"New factor","Ny faktor" "New factor","Ny faktor"
"Create factor/categorical variable from a continous variable (number/date/time).","Opret kategorisk variabel på baggrund af kontinuert variabel (numerisk/dato/tid)."
"New variable","Ny variabel" "New variable","Ny variabel"
"Create a new variable based on an R-expression.","Opret ny variabel baseret på R-kode."
"Compare modified data to original","Sammenlign ændret data med det originale datasæt" "Compare modified data to original","Sammenlign ændret data med det originale datasæt"
"Raw print of the original vs the modified data.","Simpel sammenligning af det originale og det ændrede datasæt."
"Original data:","Original data:" "Original data:","Original data:"
"Modified data:","Ændret data:" "Modified data:","Ændret data:"
"New column name:","Navn til ny variabel:" "New column name:","Navn til ny variabel:"
@ -64,7 +58,6 @@
"Imported data","Importeret data" "Imported data","Importeret data"
"www/intro.md","www/intro.md" "www/intro.md","www/intro.md"
"Choose your data","Vælg dine data" "Choose your data","Vælg dine data"
"Upload a file, get data directly from REDCap or use local or sample data.","Upload en fil, hent data direkte fra en REDCap-server eller brug test-data eller lokal data."
"Factor variable to reorder:","Kategoriske variabel der skal ændres:" "Factor variable to reorder:","Kategoriske variabel der skal ændres:"
"Sort by levels","Sorter efter niveauer" "Sort by levels","Sorter efter niveauer"
"Sort by count","Sorter efter antal" "Sort by count","Sorter efter antal"
@ -95,9 +88,7 @@
"Visuals","Grafik" "Visuals","Grafik"
"Regression","Regression" "Regression","Regression"
"Download","Download" "Download","Download"
"{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.","{data_text} har {n} observationer og {n_var} variabler, med {n_complete} ({p_complete} %) komplette cases."
"Prepare","Forbered" "Prepare","Forbered"
"At 0, only complete variables are included; at 100, all variables are included.","Ved 0 inkluderes alene komplette variabler; ved 100 inkluderes alle variabler."
"The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.","De følgende variabel-par er stærkt korrelerede: {sentence_paste(.x,and_str)}.\nOvervej at fjerne en {more}fra datasættet for at sikre at prædiktorer er internt uafhængige." "The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.","De følgende variabel-par er stærkt korrelerede: {sentence_paste(.x,and_str)}.\nOvervej at fjerne en {more}fra datasættet for at sikre at prædiktorer er internt uafhængige."
"No variables have a correlation measure above the threshold.","Ingen variabler er korrelerede over den angivne tærskelværdi." "No variables have a correlation measure above the threshold.","Ingen variabler er korrelerede over den angivne tærskelværdi."
"and","og" "and","og"
@ -141,23 +132,17 @@
"Create plot","Dan grafik" "Create plot","Dan grafik"
"Coefficients plot","Koefficientgraf" "Coefficients plot","Koefficientgraf"
"Checks","Test af model" "Checks","Test af model"
"Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters.","Nedenfor er en opsummerende tabel, der giver hurtigt overblik. Til højre kan du få et visuelt overblik, gennemgå observationer og oprette datafiltre."
"Browse observations","Gennemse observationer" "Browse observations","Gennemse observationer"
"Settings","Indstillinger" "Settings","Indstillinger"
"The following error occured on determining correlations:","Følgende fejl opstod i forbindelse med korrelationsanalysen:" "The following error occured on determining correlations:","Følgende fejl opstod i forbindelse med korrelationsanalysen:"
"We encountered the following error creating your report:","Følgende fejl opstod, da rapporten blev dannet:"
"No missing observations","Ingen manglende observationer" "No missing observations","Ingen manglende observationer"
"There is a total of {p_miss} % missing observations.","Der er i alt {p_miss} % manglende observationer." "There is a total of {p_miss} % missing observations.","Der er i alt {p_miss} % manglende observationer."
"Median:","Median:" "Median:","Median:"
"Restore original data","Gendan originale data" "Restore original data","Gendan originale data"
"Reset to original imported dataset. Careful! There is no un-doing.","Gendan det oprindeligt importerede datasæt. Forsigtig! Alle dine ændringer vil forsvinde."
"Characteristics","Karakteristika" "Characteristics","Karakteristika"
"Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list.","Alene kategoriske variabler kan danne grundlag for stratificering. Mangler du en variabel, så gå til ""Forbered"" og omklassificer til kategorisk."
"Compare strata?","Sammenlign strata?" "Compare strata?","Sammenlign strata?"
"Correlations","Korrelationer" "Correlations","Korrelationer"
"To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.","For at udelukke svarvariablen fra korrelationsanalysen, så kan du vælge din svarvariabel eller vælge 'non', hvis du ikke vil angive en."
"Correlation cut-off","Korrelationsgrænse" "Correlation cut-off","Korrelationsgrænse"
"Set the cut-off for considered 'highly correlated'.","Angiv grænsen for. hvad, der tolkes som 'betydelig korrelation'."
"Missings","Manglende observationer" "Missings","Manglende observationer"
"Class","Klasse" "Class","Klasse"
"Observations","Observationer" "Observations","Observationer"
@ -167,11 +152,9 @@
"Confirm","Bekræft" "Confirm","Bekræft"
"The filtered data","Filtreret data" "The filtered data","Filtreret data"
"Create new factor","Ny kategorisk variabel" "Create new factor","Ny kategorisk variabel"
"This window is aimed at advanced users and require some *R*-experience!","Dette vindue er primært for avancerede brugere med nogen *R*-erfaring!"
"Create new variables","Opret nye variabler" "Create new variables","Opret nye variabler"
"Select data types to include","Vælg datatyper, der skal inkluderes" "Select data types to include","Vælg datatyper, der skal inkluderes"
"Uploaded data overview","Overblik over uploaded data" "Uploaded data overview","Overblik over uploaded data"
"Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias.","Her har du en oversigt over hvordan data er blevet formateret, og hvor der er manglende observationer. Brug informationen til at overveje om manglende data mangler tilfældigt eller og der er et mønster, som kan være et udtryk for systematisk manglende data (observationsbias)."
"Specify covariables","Angiv kovariabler" "Specify covariables","Angiv kovariabler"
"If none are selected, all are included.","Hvis ingen er valgt inkluderes alle." "If none are selected, all are included.","Hvis ingen er valgt inkluderes alle."
"Analyse","Analysér" "Analyse","Analysér"
@ -209,7 +192,6 @@
"List of datasets...","Liste af datasæt..." "List of datasets...","Liste af datasæt..."
"No data selected!","Ingen data valgt!" "No data selected!","Ingen data valgt!"
"No dataset here...","Ingen datasæt her..." "No dataset here...","Ingen datasæt her..."
"Use a dataset from your environment or from the environment of a package.","Brug et datasæt fra dit lokale kodemiljø eller fra en tilgængelig pakke."
"Not a data.frame","Ikke en data.frame" "Not a data.frame","Ikke en data.frame"
"Select source","Vælg datakilde" "Select source","Vælg datakilde"
"Select a data source:","Vælg datakilde:" "Select a data source:","Vælg datakilde:"
@ -229,7 +211,6 @@
"Multivariable regression model checks","Tests af multivariabel regressionsmodel" "Multivariable regression model checks","Tests af multivariabel regressionsmodel"
"Grouped by {get_label(data,ter)}","Grupperet efter {get_label(data,ter)}" "Grouped by {get_label(data,ter)}","Grupperet efter {get_label(data,ter)}"
"Option to perform statistical comparisons between strata in baseline table.","Mulighed for at udføre statistiske tests mellem strata i oversigtstabellen." "Option to perform statistical comparisons between strata in baseline table.","Mulighed for at udføre statistiske tests mellem strata i oversigtstabellen."
"Press 'Evaluate' to create the comparison table.","Tryk 'Evaluér' for at oprette en oversigtstabel."
"The data includes {n_col} variables. Please limit to 100.","Data indeholder {n_col} variabler. Begræns venligst til 100." "The data includes {n_col} variables. Please limit to 100.","Data indeholder {n_col} variabler. Begræns venligst til 100."
"Data import","Data import" "Data import","Data import"
"Data import formatting","Formatering af data ved import" "Data import formatting","Formatering af data ved import"
@ -261,7 +242,6 @@
"By specified numbers","Efter specifikke værdier" "By specified numbers","Efter specifikke værdier"
"By quantiles (groups of equal size)","I grupper af samme størrelse" "By quantiles (groups of equal size)","I grupper af samme størrelse"
"By week number","Efter ugenummer alene" "By week number","Efter ugenummer alene"
"There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data.","Der er mere avancerede muligheder for at ændre kategoriske variable, oprette nye kategoriske variabler fra eksisterende data eller nye variable baseret på R-kode. Nederst kan du gendanne originale data."
"Split the variable","Opdel variablen" "Split the variable","Opdel variablen"
"Original data","Oprindelige data" "Original data","Oprindelige data"
"Preview of result","Forhåndsvisning af resultat" "Preview of result","Forhåndsvisning af resultat"
@ -275,7 +255,6 @@
"Browse data preview","Forhåndsvisning af resultat" "Browse data preview","Forhåndsvisning af resultat"
"Split character string","Opdel tegnstreng" "Split character string","Opdel tegnstreng"
"Split text","Opdel tekst" "Split text","Opdel tekst"
"Split a text column by a recognised delimiter.","Ingen tegnvariabler med accepterede afgrænsere fundet."
"Split a character string by a common delimiter","Opdel en tekstkolonne med en fælles afgrænser" "Split a character string by a common delimiter","Opdel en tekstkolonne med en fælles afgrænser"
"Apply split","Anvend opdeling" "Apply split","Anvend opdeling"
"Stacked relative barplot","Stablet relativt søjlediagram" "Stacked relative barplot","Stablet relativt søjlediagram"
@ -290,14 +269,10 @@
"Words","Ord" "Words","Ord"
"Shorten to first letters","Afkort til første bogstaver" "Shorten to first letters","Afkort til første bogstaver"
"Shorten to first words","Afkort til de første ord" "Shorten to first words","Afkort til de første ord"
"Missings across variables by the variable **'{input$missings_var}'**","Manglende værdier på tværs af variablerne **'{input$missings_var}'**"
"Missing vs non-missing observations in the variable **'{input$missings_var}'**","Manglende vs. ikke-manglende observationer i variablen **'{input$missings_var}'**"
"Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random.","Evaluer manglende værdier ved enten at sammenligne manglende værdier på tværs af variabler (valgfrit grupperet efter en kategorisk eller dikotom variabel) eller sammenligne variabler grupperet efter manglende status (mangler eller ej) for en udfaldsvariabel. Hvis der er en signifikant forskel i manglende værdier, kan dette forårsage en bias i dine data, og det bør overvejes omhyggeligt at fortolke dataene og analyserne, da data muligvis ikke mangler tilfældigt."
"Calculating. Hold tight for a moment..","Beregner. Hold lige fast et øjeblik.." "Calculating. Hold tight for a moment..","Beregner. Hold lige fast et øjeblik.."
"Overview of missing observations","Oversigt over manglende observationer" "Overview of missing observations","Oversigt over manglende observationer"
"Analysis method for missingness overview","Analysemetode for oversigt over manglende indhold" "Analysis method for missingness overview","Analysemetode for oversigt over manglende indhold"
"Overview of missings across variables","Oversigt over mangler på tværs af variabler" "Overview of missings across variables","Oversigt over mangler på tværs af variabler"
"Overview of difference in variables by missing status in outcome","Oversigt over forskel i variabler ved manglende status i resultat"
"Select a variable for grouped overview","Vælg en variabel til grupperet oversigt" "Select a variable for grouped overview","Vælg en variabel til grupperet oversigt"
"Select outcome variable for overview","Vælg resultatvariabel for oversigt" "Select outcome variable for overview","Vælg resultatvariabel for oversigt"
"No outcome measure chosen","Ingen resultatmål valgt" "No outcome measure chosen","Ingen resultatmål valgt"
@ -341,3 +316,14 @@
"Reorder factor levels","Omarranger niveauer" "Reorder factor levels","Omarranger niveauer"
"Modify factor levels","Modify factor levels" "Modify factor levels","Modify factor levels"
"Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables." "Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables."
"Start by loading data.","Start by loading data."
"Maximum number of observations:","Maximum number of observations:"
"setting to 0 includes all","setting to 0 includes all"
"Select a dataset from your environment or sample dataset from a package.","Select a dataset from your environment or sample dataset from a package."
"Select a sample dataset from a package.","Select a sample dataset from a package."
"Data ready to be imported!","Data ready to be imported!"
"Data has %s obs. of %s variables.","Data has %s obs. of %s variables."
"Data successfully imported!","Data successfully imported!"
"Click to see data","Click to see data"
"No data present.","No data present."
"You have provided a complete dataset with no missing values.","You have provided a complete dataset with no missing values."

1 en da
5 REDCap server export Eksport fra REDCap server
6 Local or sample data Lokal eller testdata
7 Please be mindfull handling sensitive data Pas godt på og overvej nøje hvordan du håndterer personfølsomme data
The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine). ***FreesearchR*** opbevarer alene data i forbindelse med din analyse, men du bør kun behandle personfølsomme data når du kører ***FreesearchR*** direkte på din egen maskine. [Læs mere her](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).
8 Quick overview Hurtigt overblik
9 Select variables for final import Vælg variabler til den endelige import
10 Exclude incomplete variables: Ekskluder inkomplette variabler:
23 Apply filter on observation Anvend filtre af observationer
24 Edit and create data Ændr og opret variabler
25 Subset, rename and convert variables Udvælg, omdøb og konverter variabler
Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.). Nedenfor er der mulighed for at lave simple ændringer i dit datasæt, såsom at redigere variabelnavne eller beskrivelser (bedre tabeller), eller omklassificering af variabler (numerisk, factoriel/kategorisk).
Please note that data modifications are applied before any filtering. Bemærk at alle ændringer i data anvendes inden filtreringen.
26 Advanced data manipulation Avanceret datamanipulation
27 Below options allow more advanced varaible manipulations. Nedenfor er mulighed for avancerede ændringer i data.
28 New factor Ny faktor
Create factor/categorical variable from a continous variable (number/date/time). Opret kategorisk variabel på baggrund af kontinuert variabel (numerisk/dato/tid).
29 New variable Ny variabel
Create a new variable based on an R-expression. Opret ny variabel baseret på R-kode.
30 Compare modified data to original Sammenlign ændret data med det originale datasæt
Raw print of the original vs the modified data. Simpel sammenligning af det originale og det ændrede datasæt.
31 Original data: Original data:
32 Modified data: Ændret data:
33 New column name: Navn til ny variabel:
58 Imported data Importeret data
59 www/intro.md www/intro.md
60 Choose your data Vælg dine data
Upload a file, get data directly from REDCap or use local or sample data. Upload en fil, hent data direkte fra en REDCap-server eller brug test-data eller lokal data.
61 Factor variable to reorder: Kategoriske variabel der skal ændres:
62 Sort by levels Sorter efter niveauer
63 Sort by count Sorter efter antal
88 Visuals Grafik
89 Regression Regression
90 Download Download
{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases. {data_text} har {n} observationer og {n_var} variabler, med {n_complete} ({p_complete} %) komplette cases.
91 Prepare Forbered
At 0, only complete variables are included; at 100, all variables are included. Ved 0 inkluderes alene komplette variabler; ved 100 inkluderes alle variabler.
92 The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent. De følgende variabel-par er stærkt korrelerede: {sentence_paste(.x,and_str)}.\nOvervej at fjerne en {more}fra datasættet for at sikre at prædiktorer er internt uafhængige.
93 No variables have a correlation measure above the threshold. Ingen variabler er korrelerede over den angivne tærskelværdi.
94 and og
132 Create plot Dan grafik
133 Coefficients plot Koefficientgraf
134 Checks Test af model
Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters. Nedenfor er en opsummerende tabel, der giver hurtigt overblik. Til højre kan du få et visuelt overblik, gennemgå observationer og oprette datafiltre.
135 Browse observations Gennemse observationer
136 Settings Indstillinger
137 The following error occured on determining correlations: Følgende fejl opstod i forbindelse med korrelationsanalysen:
We encountered the following error creating your report: Følgende fejl opstod, da rapporten blev dannet:
138 No missing observations Ingen manglende observationer
139 There is a total of {p_miss} % missing observations. Der er i alt {p_miss} % manglende observationer.
140 Median: Median:
141 Restore original data Gendan originale data
Reset to original imported dataset. Careful! There is no un-doing. Gendan det oprindeligt importerede datasæt. Forsigtig! Alle dine ændringer vil forsvinde.
142 Characteristics Karakteristika
Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list. Alene kategoriske variabler kan danne grundlag for stratificering. Mangler du en variabel, så gå til "Forbered" og omklassificer til kategorisk.
143 Compare strata? Sammenlign strata?
144 Correlations Korrelationer
To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'. For at udelukke svarvariablen fra korrelationsanalysen, så kan du vælge din svarvariabel eller vælge 'non', hvis du ikke vil angive en.
145 Correlation cut-off Korrelationsgrænse
Set the cut-off for considered 'highly correlated'. Angiv grænsen for. hvad, der tolkes som 'betydelig korrelation'.
146 Missings Manglende observationer
147 Class Klasse
148 Observations Observationer
152 Confirm Bekræft
153 The filtered data Filtreret data
154 Create new factor Ny kategorisk variabel
This window is aimed at advanced users and require some *R*-experience! Dette vindue er primært for avancerede brugere med nogen *R*-erfaring!
155 Create new variables Opret nye variabler
156 Select data types to include Vælg datatyper, der skal inkluderes
157 Uploaded data overview Overblik over uploaded data
Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias. Her har du en oversigt over hvordan data er blevet formateret, og hvor der er manglende observationer. Brug informationen til at overveje om manglende data mangler tilfældigt eller og der er et mønster, som kan være et udtryk for systematisk manglende data (observationsbias).
158 Specify covariables Angiv kovariabler
159 If none are selected, all are included. Hvis ingen er valgt inkluderes alle.
160 Analyse Analysér
192 List of datasets... Liste af datasæt...
193 No data selected! Ingen data valgt!
194 No dataset here... Ingen datasæt her...
Use a dataset from your environment or from the environment of a package. Brug et datasæt fra dit lokale kodemiljø eller fra en tilgængelig pakke.
195 Not a data.frame Ikke en data.frame
196 Select source Vælg datakilde
197 Select a data source: Vælg datakilde:
211 Multivariable regression model checks Tests af multivariabel regressionsmodel
212 Grouped by {get_label(data,ter)} Grupperet efter {get_label(data,ter)}
213 Option to perform statistical comparisons between strata in baseline table. Mulighed for at udføre statistiske tests mellem strata i oversigtstabellen.
Press 'Evaluate' to create the comparison table. Tryk 'Evaluér' for at oprette en oversigtstabel.
214 The data includes {n_col} variables. Please limit to 100. Data indeholder {n_col} variabler. Begræns venligst til 100.
215 Data import Data import
216 Data import formatting Formatering af data ved import
242 By specified numbers Efter specifikke værdier
243 By quantiles (groups of equal size) I grupper af samme størrelse
244 By week number Efter ugenummer alene
There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data. Der er mere avancerede muligheder for at ændre kategoriske variable, oprette nye kategoriske variabler fra eksisterende data eller nye variable baseret på R-kode. Nederst kan du gendanne originale data.
245 Split the variable Opdel variablen
246 Original data Oprindelige data
247 Preview of result Forhåndsvisning af resultat
255 Browse data preview Forhåndsvisning af resultat
256 Split character string Opdel tegnstreng
257 Split text Opdel tekst
Split a text column by a recognised delimiter. Ingen tegnvariabler med accepterede afgrænsere fundet.
258 Split a character string by a common delimiter Opdel en tekstkolonne med en fælles afgrænser
259 Apply split Anvend opdeling
260 Stacked relative barplot Stablet relativt søjlediagram
269 Words Ord
270 Shorten to first letters Afkort til første bogstaver
271 Shorten to first words Afkort til de første ord
Missings across variables by the variable **'{input$missings_var}'** Manglende værdier på tværs af variablerne **'{input$missings_var}'**
Missing vs non-missing observations in the variable **'{input$missings_var}'** Manglende vs. ikke-manglende observationer i variablen **'{input$missings_var}'**
Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random. Evaluer manglende værdier ved enten at sammenligne manglende værdier på tværs af variabler (valgfrit grupperet efter en kategorisk eller dikotom variabel) eller sammenligne variabler grupperet efter manglende status (mangler eller ej) for en udfaldsvariabel. Hvis der er en signifikant forskel i manglende værdier, kan dette forårsage en bias i dine data, og det bør overvejes omhyggeligt at fortolke dataene og analyserne, da data muligvis ikke mangler tilfældigt.
272 Calculating. Hold tight for a moment.. Beregner. Hold lige fast et øjeblik..
273 Overview of missing observations Oversigt over manglende observationer
274 Analysis method for missingness overview Analysemetode for oversigt over manglende indhold
275 Overview of missings across variables Oversigt over mangler på tværs af variabler
Overview of difference in variables by missing status in outcome Oversigt over forskel i variabler ved manglende status i resultat
276 Select a variable for grouped overview Vælg en variabel til grupperet oversigt
277 Select outcome variable for overview Vælg resultatvariabel for oversigt
278 No outcome measure chosen Ingen resultatmål valgt
316 Reorder factor levels Omarranger niveauer
317 Modify factor levels Modify factor levels
318 Reorder or rename the levels of factor/categorical variables. Reorder or rename the levels of factor/categorical variables.
319 Start by loading data. Start by loading data.
320 Maximum number of observations: Maximum number of observations:
321 setting to 0 includes all setting to 0 includes all
322 Select a dataset from your environment or sample dataset from a package. Select a dataset from your environment or sample dataset from a package.
323 Select a sample dataset from a package. Select a sample dataset from a package.
324 Data ready to be imported! Data ready to be imported!
325 Data has %s obs. of %s variables. Data has %s obs. of %s variables.
326 Data successfully imported! Data successfully imported!
327 Click to see data Click to see data
328 No data present. No data present.
329 You have provided a complete dataset with no missing values. You have provided a complete dataset with no missing values.

36
app_docker/translations/translation_sw.csv
View file

@ -5,7 +5,6 @@
"REDCap server export","Usafirishaji wa seva ya REDCap" "REDCap server export","Usafirishaji wa seva ya REDCap"
"Local or sample data","Data ya ndani au ya sampuli" "Local or sample data","Data ya ndani au ya sampuli"
"Please be mindfull handling sensitive data","Tafadhali kuwa mwangalifu kushughulikia data nyeti" "Please be mindfull handling sensitive data","Tafadhali kuwa mwangalifu kushughulikia data nyeti"
"The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).","Programu ya ***FreesearchR*** huhifadhi data kwa ajili ya uchambuzi pekee, lakini tafadhali tumia tu na data nyeti unapoendesha ndani. [Soma zaidi hapa](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine)."
"Quick overview","Muhtasari wa haraka" "Quick overview","Muhtasari wa haraka"
"Select variables for final import","Chagua vigezo vya kuingiza mwisho" "Select variables for final import","Chagua vigezo vya kuingiza mwisho"
"Exclude incomplete variables:","Ondoa vigezo visivyokamilika:" "Exclude incomplete variables:","Ondoa vigezo visivyokamilika:"
@ -24,16 +23,11 @@
"Apply filter on observation","Tumia kichujio wakati wa uchunguzi" "Apply filter on observation","Tumia kichujio wakati wa uchunguzi"
"Edit and create data","Hariri na uunde data" "Edit and create data","Hariri na uunde data"
"Subset, rename and convert variables","Weka sehemu ndogo, badilisha jina na ubadilishe vigezo" "Subset, rename and convert variables","Weka sehemu ndogo, badilisha jina na ubadilishe vigezo"
"Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.).","Hapa chini, kuna chaguo kadhaa za urekebishaji rahisi wa data kama vile kusasisha vigezo kwa kubadilisha majina, kuunda lebo mpya (kwa majedwali mazuri zaidi katika ripoti) na kubadilisha madarasa ya vigezo (nambari, vipengele/kategoria n.k.)."
"Please note that data modifications are applied before any filtering.","Tafadhali kumbuka kwamba marekebisho ya data hutumika kabla ya kuchuja yoyote."
"Advanced data manipulation","Udhibiti wa data wa hali ya juu" "Advanced data manipulation","Udhibiti wa data wa hali ya juu"
"Below options allow more advanced varaible manipulations.","Chaguzi zilizo hapa chini huruhusu udanganyifu wa hali ya juu zaidi unaoweza kubadilika." "Below options allow more advanced varaible manipulations.","Chaguzi zilizo hapa chini huruhusu udanganyifu wa hali ya juu zaidi unaoweza kubadilika."
"New factor","Kipengele kipya" "New factor","Kipengele kipya"
"Create factor/categorical variable from a continous variable (number/date/time).","Unda kigezo cha kipengele/kitengo kutoka kwa kigezo endelevu (nambari/tarehe/saa)."
"New variable","Kigezo kipya" "New variable","Kigezo kipya"
"Create a new variable based on an R-expression.","Unda kigezo kipya kulingana na usemi wa R."
"Compare modified data to original","Linganisha data iliyobadilishwa na ya asili" "Compare modified data to original","Linganisha data iliyobadilishwa na ya asili"
"Raw print of the original vs the modified data.","Chapisho ghafi la data asili dhidi ya data iliyorekebishwa."
"Original data:","Data asilia:" "Original data:","Data asilia:"
"Modified data:","Data iliyorekebishwa:" "Modified data:","Data iliyorekebishwa:"
"New column name:","Jina jipya la safu wima:" "New column name:","Jina jipya la safu wima:"
@ -64,7 +58,6 @@
"Imported data","Data iliyoingizwa" "Imported data","Data iliyoingizwa"
"www/intro.md","www/intro.md" "www/intro.md","www/intro.md"
"Choose your data","Chagua data yako" "Choose your data","Chagua data yako"
"Upload a file, get data directly from REDCap or use local or sample data.","Pakia faili, pata data moja kwa moja kutoka REDCap au tumia data ya ndani au sampuli."
"Factor variable to reorder:","Kigezo cha vipengele ili kupanga upya:" "Factor variable to reorder:","Kigezo cha vipengele ili kupanga upya:"
"Sort by levels","Panga kwa viwango" "Sort by levels","Panga kwa viwango"
"Sort by count","Panga kwa hesabu" "Sort by count","Panga kwa hesabu"
@ -95,9 +88,7 @@
"Visuals","Picha" "Visuals","Picha"
"Regression","Urejeshaji" "Regression","Urejeshaji"
"Download","Pakua" "Download","Pakua"
"{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.","{data_text} ina uchunguzi wa {n} na vigezo vya {n_var}, pamoja na visa kamili vya {n_complete} ({p_complete}%)."
"Prepare","Tayarisha" "Prepare","Tayarisha"
"At 0, only complete variables are included; at 100, all variables are included.","Katika 0, ni vigezo kamili pekee vilivyojumuishwa; katika 100, vigezo vyote vimejumuishwa."
"The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.","Jozi zifuatazo za vigeu zina uhusiano wa hali ya juu: {sentence_paste(.x,and_str)}.\nFikiria kutenga moja {zaidi} kutoka kwenye seti ya data ili kuhakikisha vigeu vinajitegemea." "The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.","Jozi zifuatazo za vigeu zina uhusiano wa hali ya juu: {sentence_paste(.x,and_str)}.\nFikiria kutenga moja {zaidi} kutoka kwenye seti ya data ili kuhakikisha vigeu vinajitegemea."
"No variables have a correlation measure above the threshold.","Hakuna vigezo vyenye kipimo cha uhusiano kilicho juu ya kizingiti." "No variables have a correlation measure above the threshold.","Hakuna vigezo vyenye kipimo cha uhusiano kilicho juu ya kizingiti."
"and","na" "and","na"
@ -141,23 +132,17 @@
"Create plot","Unda njama" "Create plot","Unda njama"
"Coefficients plot","Mchoro wa viambato" "Coefficients plot","Mchoro wa viambato"
"Checks","Hundi" "Checks","Hundi"
"Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters.","Hapa chini kuna jedwali la muhtasari kwa ajili ya ufahamu wa haraka, na upande wa kulia unaweza kuibua madarasa ya data, kuvinjari uchunguzi na kutumia vichujio tofauti vya data."
"Browse observations","Vinjari uchunguzi" "Browse observations","Vinjari uchunguzi"
"Settings","Mipangilio" "Settings","Mipangilio"
"The following error occured on determining correlations:","Hitilafu ifuatayo ilitokea katika kubaini uhusiano:" "The following error occured on determining correlations:","Hitilafu ifuatayo ilitokea katika kubaini uhusiano:"
"We encountered the following error creating your report:","Tulikutana na hitilafu ifuatayo katika kuunda ripoti yako:"
"No missing observations","Hakuna uchunguzi unaokosekana" "No missing observations","Hakuna uchunguzi unaokosekana"
"There is a total of {p_miss} % missing observations.","Kuna jumla ya uchunguzi wa {p_miss}% unaokosekana." "There is a total of {p_miss} % missing observations.","Kuna jumla ya uchunguzi wa {p_miss}% unaokosekana."
"Median:","Wastani:" "Median:","Wastani:"
"Restore original data","Rejesha data asili" "Restore original data","Rejesha data asili"
"Reset to original imported dataset. Careful! There is no un-doing.","Rudisha kwenye seti ya data asili iliyoingizwa. Kuwa mwangalifu! Hakuna kutengua."
"Characteristics","Sifa" "Characteristics","Sifa"
"Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list.","Vigezo vya vipengele/kategoria pekee ndivyo vinavyopatikana kwa ajili ya uainishaji wa tabaka. Rudi kwenye kichupo cha 'Tayarisha' ili kupanga upya kigezo ikiwa hakipo kwenye orodha."
"Compare strata?","Linganisha tabaka?" "Compare strata?","Linganisha tabaka?"
"Correlations","Uhusiano" "Correlations","Uhusiano"
"To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.","Ili kuepuka kutathmini uhusiano wa kigezo cha matokeo, hii inaweza kutengwa kwenye njama au kuchagua 'hakuna'."
"Correlation cut-off","Kikomo cha uhusiano" "Correlation cut-off","Kikomo cha uhusiano"
"Set the cut-off for considered 'highly correlated'.","Weka kikomo cha 'kinachohusiana sana'."
"Missings","Hazipo" "Missings","Hazipo"
"Class","Darasa" "Class","Darasa"
"Observations","Uchunguzi" "Observations","Uchunguzi"
@ -167,11 +152,9 @@
"Confirm","Thibitisha" "Confirm","Thibitisha"
"The filtered data","Data iliyochujwa" "The filtered data","Data iliyochujwa"
"Create new factor","Unda kipengele kipya" "Create new factor","Unda kipengele kipya"
"This window is aimed at advanced users and require some *R*-experience!","Dirisha hili linalenga watumiaji wa hali ya juu na linahitaji uzoefu wa *R*!"
"Create new variables","Unda vigezo vipya" "Create new variables","Unda vigezo vipya"
"Select data types to include","Chagua aina za data za kujumuisha" "Select data types to include","Chagua aina za data za kujumuisha"
"Uploaded data overview","Muhtasari wa data iliyopakiwa" "Uploaded data overview","Muhtasari wa data iliyopakiwa"
"Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias.","Hapa kuna muhtasari wa jinsi data yako inavyotafsiriwa, na mahali ambapo data inakosekana. Tumia taarifa hii kuzingatia ikiwa data inakosekana bila mpangilio au ikiwa baadhi ya uchunguzi unakosekana kimfumo ambao unaweza kusababishwa na upendeleo wa uchunguzi."
"Specify covariables","Bainisha vigeu vinavyoweza kuunganishwa" "Specify covariables","Bainisha vigeu vinavyoweza kuunganishwa"
"If none are selected, all are included.","Ikiwa hakuna aliyechaguliwa, wote wamejumuishwa." "If none are selected, all are included.","Ikiwa hakuna aliyechaguliwa, wote wamejumuishwa."
"Analyse","Changanua" "Analyse","Changanua"
@ -209,7 +192,6 @@
"List of datasets...","Orodha ya seti za data..." "List of datasets...","Orodha ya seti za data..."
"No data selected!","Hakuna data iliyochaguliwa!" "No data selected!","Hakuna data iliyochaguliwa!"
"No dataset here...","Hakuna seti ya data hapa..." "No dataset here...","Hakuna seti ya data hapa..."
"Use a dataset from your environment or from the environment of a package.","Tumia seti ya data kutoka kwa mazingira yako au kutoka kwa mazingira ya kifurushi."
"Not a data.frame","Sio data.frame" "Not a data.frame","Sio data.frame"
"Select source","Chagua chanzo" "Select source","Chagua chanzo"
"Select a data source:","Chagua chanzo cha data:" "Select a data source:","Chagua chanzo cha data:"
@ -229,7 +211,6 @@
"Multivariable regression model checks","Ukaguzi wa modeli ya urejeshaji unaoweza kubadilika-badilika" "Multivariable regression model checks","Ukaguzi wa modeli ya urejeshaji unaoweza kubadilika-badilika"
"Grouped by {get_label(data,ter)}","Imepangwa kwa makundi kulingana na {get_label(data,ter)}" "Grouped by {get_label(data,ter)}","Imepangwa kwa makundi kulingana na {get_label(data,ter)}"
"Option to perform statistical comparisons between strata in baseline table.","Chaguo la kufanya ulinganisho wa takwimu kati ya tabaka katika jedwali la msingi." "Option to perform statistical comparisons between strata in baseline table.","Chaguo la kufanya ulinganisho wa takwimu kati ya tabaka katika jedwali la msingi."
"Press 'Evaluate' to create the comparison table.","Bonyeza 'Tathmini' ili kuunda jedwali la kulinganisha."
"The data includes {n_col} variables. Please limit to 100.","Data inajumuisha vigezo vya {n_col}. Tafadhali punguza hadi 100." "The data includes {n_col} variables. Please limit to 100.","Data inajumuisha vigezo vya {n_col}. Tafadhali punguza hadi 100."
"Data import","Uingizaji wa data" "Data import","Uingizaji wa data"
"Data import formatting","Uumbizaji wa kuingiza data" "Data import formatting","Uumbizaji wa kuingiza data"
@ -261,7 +242,6 @@
"By specified numbers","Kwa nambari zilizoainishwa" "By specified numbers","Kwa nambari zilizoainishwa"
"By quantiles (groups of equal size)","Kwa quantiles (vikundi vya ukubwa sawa)" "By quantiles (groups of equal size)","Kwa quantiles (vikundi vya ukubwa sawa)"
"Please fill in web address and API token, then press 'Connect'.","Tafadhali jaza anwani ya wavuti na tokeni ya API, kisha bonyeza 'Unganisha'." "Please fill in web address and API token, then press 'Connect'.","Tafadhali jaza anwani ya wavuti na tokeni ya API, kisha bonyeza 'Unganisha'."
"There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data.","Kuna chaguo za hali ya juu zaidi za kurekebisha vigezo vya vipengele/kategoria pamoja na kuunda kipengele kipya kutoka kwa kigezo kilichopo au vigezo vipya vyenye msimbo wa R. Chini unaweza kurejesha data asili."
"Text or character to split string by","Maandishi au herufi ya kugawanya mfuatano kwa" "Text or character to split string by","Maandishi au herufi ya kugawanya mfuatano kwa"
"Split the variable","Gawanya kigezo" "Split the variable","Gawanya kigezo"
"Variable to split:","Kinachoweza kubadilika hadi kugawanyika:" "Variable to split:","Kinachoweza kubadilika hadi kugawanyika:"
@ -276,7 +256,6 @@
"Original data","Data asili" "Original data","Data asili"
"Preview of result","Hakikisho la matokeo" "Preview of result","Hakikisho la matokeo"
"No character variables with accepted delimiters detected.","Hakuna vigezo vya herufi vilivyo na vidhibiti vinavyokubalika vilivyogunduliwa." "No character variables with accepted delimiters detected.","Hakuna vigezo vya herufi vilivyo na vidhibiti vinavyokubalika vilivyogunduliwa."
"Split a text column by a recognised delimiter.","Gawanya safu wima ya maandishi kwa kitenga kinachotambulika."
"Apply split","Tumia mgawanyiko" "Apply split","Tumia mgawanyiko"
"Stacked relative barplot","Kipande cha baruni kilichopangwa kwa mirundiko" "Stacked relative barplot","Kipande cha baruni kilichopangwa kwa mirundiko"
"Create relative stacked barplots to show the distribution of categorical levels","Unda viwanja vya baruni vilivyopangwa ili kuonyesha usambazaji wa viwango vya kategoria" "Create relative stacked barplots to show the distribution of categorical levels","Unda viwanja vya baruni vilivyopangwa ili kuonyesha usambazaji wa viwango vya kategoria"
@ -290,14 +269,10 @@
"Words","Maneno" "Words","Maneno"
"Shorten to first letters","Fupisha herufi za kwanza" "Shorten to first letters","Fupisha herufi za kwanza"
"Shorten to first words","Fupisha maneno ya kwanza" "Shorten to first words","Fupisha maneno ya kwanza"
"Missings across variables by the variable **'{input$missings_var}'**","Hazipo katika vigezo kwa kigezo **'{input$missings_var}'**"
"Missing vs non-missing observations in the variable **'{input$missings_var}'**","Uchunguzi unaokosekana dhidi ya usiokosekana katika kigezo **'{input$missings_var}'**"
"Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random.","Tathmini upungufu kwa kulinganisha thamani zinazokosekana katika vigezo (hiari zilizopangwa kwa mujibu wa kigezo cha kategoria au cha pande mbili) au linganisha vigezo vilivyopangwa kwa mujibu wa hali inayokosekana (inayokosekana au isiyokosekana) ya kigezo cha matokeo. Ikiwa kuna tofauti kubwa katika upungufu, hii inaweza kusababisha upendeleo katika data yako na inapaswa kuzingatiwa kwa uangalifu kutafsiri data na uchambuzi kwani data inaweza isikosekane bila mpangilio."
"Calculating. Hold tight for a moment..","Kuhesabu. Shikilia kwa muda.." "Calculating. Hold tight for a moment..","Kuhesabu. Shikilia kwa muda.."
"Overview of missing observations","Muhtasari wa uchunguzi uliokosekana" "Overview of missing observations","Muhtasari wa uchunguzi uliokosekana"
"Analysis method for missingness overview","Mbinu ya uchambuzi wa muhtasari wa kukosekana" "Analysis method for missingness overview","Mbinu ya uchambuzi wa muhtasari wa kukosekana"
"Overview of missings across variables","Muhtasari wa mambo yanayokosekana katika vigezo" "Overview of missings across variables","Muhtasari wa mambo yanayokosekana katika vigezo"
"Overview of difference in variables by missing status in outcome","Muhtasari wa tofauti katika vigezo kwa kukosa hali katika matokeo"
"Select a variable for grouped overview","Chagua kigezo cha muhtasari wa kikundi" "Select a variable for grouped overview","Chagua kigezo cha muhtasari wa kikundi"
"Select outcome variable for overview","Chagua kigezo cha matokeo kwa muhtasari" "Select outcome variable for overview","Chagua kigezo cha matokeo kwa muhtasari"
"No outcome measure chosen","Hakuna kipimo cha matokeo kilichochaguliwa" "No outcome measure chosen","Hakuna kipimo cha matokeo kilichochaguliwa"
@ -341,3 +316,14 @@
"Reorder factor levels","Reorder factor levels" "Reorder factor levels","Reorder factor levels"
"Modify factor levels","Modify factor levels" "Modify factor levels","Modify factor levels"
"Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables." "Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables."
"Start by loading data.","Start by loading data."
"Maximum number of observations:","Maximum number of observations:"
"setting to 0 includes all","setting to 0 includes all"
"Select a dataset from your environment or sample dataset from a package.","Select a dataset from your environment or sample dataset from a package."
"Select a sample dataset from a package.","Select a sample dataset from a package."
"Data ready to be imported!","Data ready to be imported!"
"Data has %s obs. of %s variables.","Data has %s obs. of %s variables."
"Data successfully imported!","Data successfully imported!"
"Click to see data","Click to see data"
"No data present.","No data present."
"You have provided a complete dataset with no missing values.","You have provided a complete dataset with no missing values."

1 en sw
5 REDCap server export Usafirishaji wa seva ya REDCap
6 Local or sample data Data ya ndani au ya sampuli
7 Please be mindfull handling sensitive data Tafadhali kuwa mwangalifu kushughulikia data nyeti
The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine). Programu ya ***FreesearchR*** huhifadhi data kwa ajili ya uchambuzi pekee, lakini tafadhali tumia tu na data nyeti unapoendesha ndani. [Soma zaidi hapa](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).
8 Quick overview Muhtasari wa haraka
9 Select variables for final import Chagua vigezo vya kuingiza mwisho
10 Exclude incomplete variables: Ondoa vigezo visivyokamilika:
23 Apply filter on observation Tumia kichujio wakati wa uchunguzi
24 Edit and create data Hariri na uunde data
25 Subset, rename and convert variables Weka sehemu ndogo, badilisha jina na ubadilishe vigezo
Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.). Hapa chini, kuna chaguo kadhaa za urekebishaji rahisi wa data kama vile kusasisha vigezo kwa kubadilisha majina, kuunda lebo mpya (kwa majedwali mazuri zaidi katika ripoti) na kubadilisha madarasa ya vigezo (nambari, vipengele/kategoria n.k.).
Please note that data modifications are applied before any filtering. Tafadhali kumbuka kwamba marekebisho ya data hutumika kabla ya kuchuja yoyote.
26 Advanced data manipulation Udhibiti wa data wa hali ya juu
27 Below options allow more advanced varaible manipulations. Chaguzi zilizo hapa chini huruhusu udanganyifu wa hali ya juu zaidi unaoweza kubadilika.
28 New factor Kipengele kipya
Create factor/categorical variable from a continous variable (number/date/time). Unda kigezo cha kipengele/kitengo kutoka kwa kigezo endelevu (nambari/tarehe/saa).
29 New variable Kigezo kipya
Create a new variable based on an R-expression. Unda kigezo kipya kulingana na usemi wa R.
30 Compare modified data to original Linganisha data iliyobadilishwa na ya asili
Raw print of the original vs the modified data. Chapisho ghafi la data asili dhidi ya data iliyorekebishwa.
31 Original data: Data asilia:
32 Modified data: Data iliyorekebishwa:
33 New column name: Jina jipya la safu wima:
58 Imported data Data iliyoingizwa
59 www/intro.md www/intro.md
60 Choose your data Chagua data yako
Upload a file, get data directly from REDCap or use local or sample data. Pakia faili, pata data moja kwa moja kutoka REDCap au tumia data ya ndani au sampuli.
61 Factor variable to reorder: Kigezo cha vipengele ili kupanga upya:
62 Sort by levels Panga kwa viwango
63 Sort by count Panga kwa hesabu
88 Visuals Picha
89 Regression Urejeshaji
90 Download Pakua
{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases. {data_text} ina uchunguzi wa {n} na vigezo vya {n_var}, pamoja na visa kamili vya {n_complete} ({p_complete}%).
91 Prepare Tayarisha
At 0, only complete variables are included; at 100, all variables are included. Katika 0, ni vigezo kamili pekee vilivyojumuishwa; katika 100, vigezo vyote vimejumuishwa.
92 The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent. Jozi zifuatazo za vigeu zina uhusiano wa hali ya juu: {sentence_paste(.x,and_str)}.\nFikiria kutenga moja {zaidi} kutoka kwenye seti ya data ili kuhakikisha vigeu vinajitegemea.
93 No variables have a correlation measure above the threshold. Hakuna vigezo vyenye kipimo cha uhusiano kilicho juu ya kizingiti.
94 and na
132 Create plot Unda njama
133 Coefficients plot Mchoro wa viambato
134 Checks Hundi
Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters. Hapa chini kuna jedwali la muhtasari kwa ajili ya ufahamu wa haraka, na upande wa kulia unaweza kuibua madarasa ya data, kuvinjari uchunguzi na kutumia vichujio tofauti vya data.
135 Browse observations Vinjari uchunguzi
136 Settings Mipangilio
137 The following error occured on determining correlations: Hitilafu ifuatayo ilitokea katika kubaini uhusiano:
We encountered the following error creating your report: Tulikutana na hitilafu ifuatayo katika kuunda ripoti yako:
138 No missing observations Hakuna uchunguzi unaokosekana
139 There is a total of {p_miss} % missing observations. Kuna jumla ya uchunguzi wa {p_miss}% unaokosekana.
140 Median: Wastani:
141 Restore original data Rejesha data asili
Reset to original imported dataset. Careful! There is no un-doing. Rudisha kwenye seti ya data asili iliyoingizwa. Kuwa mwangalifu! Hakuna kutengua.
142 Characteristics Sifa
Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list. Vigezo vya vipengele/kategoria pekee ndivyo vinavyopatikana kwa ajili ya uainishaji wa tabaka. Rudi kwenye kichupo cha 'Tayarisha' ili kupanga upya kigezo ikiwa hakipo kwenye orodha.
143 Compare strata? Linganisha tabaka?
144 Correlations Uhusiano
To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'. Ili kuepuka kutathmini uhusiano wa kigezo cha matokeo, hii inaweza kutengwa kwenye njama au kuchagua 'hakuna'.
145 Correlation cut-off Kikomo cha uhusiano
Set the cut-off for considered 'highly correlated'. Weka kikomo cha 'kinachohusiana sana'.
146 Missings Hazipo
147 Class Darasa
148 Observations Uchunguzi
152 Confirm Thibitisha
153 The filtered data Data iliyochujwa
154 Create new factor Unda kipengele kipya
This window is aimed at advanced users and require some *R*-experience! Dirisha hili linalenga watumiaji wa hali ya juu na linahitaji uzoefu wa *R*!
155 Create new variables Unda vigezo vipya
156 Select data types to include Chagua aina za data za kujumuisha
157 Uploaded data overview Muhtasari wa data iliyopakiwa
Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias. Hapa kuna muhtasari wa jinsi data yako inavyotafsiriwa, na mahali ambapo data inakosekana. Tumia taarifa hii kuzingatia ikiwa data inakosekana bila mpangilio au ikiwa baadhi ya uchunguzi unakosekana kimfumo ambao unaweza kusababishwa na upendeleo wa uchunguzi.
158 Specify covariables Bainisha vigeu vinavyoweza kuunganishwa
159 If none are selected, all are included. Ikiwa hakuna aliyechaguliwa, wote wamejumuishwa.
160 Analyse Changanua
192 List of datasets... Orodha ya seti za data...
193 No data selected! Hakuna data iliyochaguliwa!
194 No dataset here... Hakuna seti ya data hapa...
Use a dataset from your environment or from the environment of a package. Tumia seti ya data kutoka kwa mazingira yako au kutoka kwa mazingira ya kifurushi.
195 Not a data.frame Sio data.frame
196 Select source Chagua chanzo
197 Select a data source: Chagua chanzo cha data:
211 Multivariable regression model checks Ukaguzi wa modeli ya urejeshaji unaoweza kubadilika-badilika
212 Grouped by {get_label(data,ter)} Imepangwa kwa makundi kulingana na {get_label(data,ter)}
213 Option to perform statistical comparisons between strata in baseline table. Chaguo la kufanya ulinganisho wa takwimu kati ya tabaka katika jedwali la msingi.
Press 'Evaluate' to create the comparison table. Bonyeza 'Tathmini' ili kuunda jedwali la kulinganisha.
214 The data includes {n_col} variables. Please limit to 100. Data inajumuisha vigezo vya {n_col}. Tafadhali punguza hadi 100.
215 Data import Uingizaji wa data
216 Data import formatting Uumbizaji wa kuingiza data
242 By specified numbers Kwa nambari zilizoainishwa
243 By quantiles (groups of equal size) Kwa quantiles (vikundi vya ukubwa sawa)
244 Please fill in web address and API token, then press 'Connect'. Tafadhali jaza anwani ya wavuti na tokeni ya API, kisha bonyeza 'Unganisha'.
There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data. Kuna chaguo za hali ya juu zaidi za kurekebisha vigezo vya vipengele/kategoria pamoja na kuunda kipengele kipya kutoka kwa kigezo kilichopo au vigezo vipya vyenye msimbo wa R. Chini unaweza kurejesha data asili.
245 Text or character to split string by Maandishi au herufi ya kugawanya mfuatano kwa
246 Split the variable Gawanya kigezo
247 Variable to split: Kinachoweza kubadilika hadi kugawanyika:
256 Original data Data asili
257 Preview of result Hakikisho la matokeo
258 No character variables with accepted delimiters detected. Hakuna vigezo vya herufi vilivyo na vidhibiti vinavyokubalika vilivyogunduliwa.
Split a text column by a recognised delimiter. Gawanya safu wima ya maandishi kwa kitenga kinachotambulika.
259 Apply split Tumia mgawanyiko
260 Stacked relative barplot Kipande cha baruni kilichopangwa kwa mirundiko
261 Create relative stacked barplots to show the distribution of categorical levels Unda viwanja vya baruni vilivyopangwa ili kuonyesha usambazaji wa viwango vya kategoria
269 Words Maneno
270 Shorten to first letters Fupisha herufi za kwanza
271 Shorten to first words Fupisha maneno ya kwanza
Missings across variables by the variable **'{input$missings_var}'** Hazipo katika vigezo kwa kigezo **'{input$missings_var}'**
Missing vs non-missing observations in the variable **'{input$missings_var}'** Uchunguzi unaokosekana dhidi ya usiokosekana katika kigezo **'{input$missings_var}'**
Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random. Tathmini upungufu kwa kulinganisha thamani zinazokosekana katika vigezo (hiari zilizopangwa kwa mujibu wa kigezo cha kategoria au cha pande mbili) au linganisha vigezo vilivyopangwa kwa mujibu wa hali inayokosekana (inayokosekana au isiyokosekana) ya kigezo cha matokeo. Ikiwa kuna tofauti kubwa katika upungufu, hii inaweza kusababisha upendeleo katika data yako na inapaswa kuzingatiwa kwa uangalifu kutafsiri data na uchambuzi kwani data inaweza isikosekane bila mpangilio.
272 Calculating. Hold tight for a moment.. Kuhesabu. Shikilia kwa muda..
273 Overview of missing observations Muhtasari wa uchunguzi uliokosekana
274 Analysis method for missingness overview Mbinu ya uchambuzi wa muhtasari wa kukosekana
275 Overview of missings across variables Muhtasari wa mambo yanayokosekana katika vigezo
Overview of difference in variables by missing status in outcome Muhtasari wa tofauti katika vigezo kwa kukosa hali katika matokeo
276 Select a variable for grouped overview Chagua kigezo cha muhtasari wa kikundi
277 Select outcome variable for overview Chagua kigezo cha matokeo kwa muhtasari
278 No outcome measure chosen Hakuna kipimo cha matokeo kilichochaguliwa
316 Reorder factor levels Reorder factor levels
317 Modify factor levels Modify factor levels
318 Reorder or rename the levels of factor/categorical variables. Reorder or rename the levels of factor/categorical variables.
319 Start by loading data. Start by loading data.
320 Maximum number of observations: Maximum number of observations:
321 setting to 0 includes all setting to 0 includes all
322 Select a dataset from your environment or sample dataset from a package. Select a dataset from your environment or sample dataset from a package.
323 Select a sample dataset from a package. Select a sample dataset from a package.
324 Data ready to be imported! Data ready to be imported!
325 Data has %s obs. of %s variables. Data has %s obs. of %s variables.
326 Data successfully imported! Data successfully imported!
327 Click to see data Click to see data
328 No data present. No data present.
329 You have provided a complete dataset with no missing values. You have provided a complete dataset with no missing values.

2210
inst/apps/FreesearchR/app.R
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File diff suppressed because it is too large Load diff

36
inst/translations/translation_da.csv
View file

@ -5,7 +5,6 @@
"REDCap server export","Eksport fra REDCap server" "REDCap server export","Eksport fra REDCap server"
"Local or sample data","Lokal eller testdata" "Local or sample data","Lokal eller testdata"
"Please be mindfull handling sensitive data","Pas godt på og overvej nøje hvordan du håndterer personfølsomme data" "Please be mindfull handling sensitive data","Pas godt på og overvej nøje hvordan du håndterer personfølsomme data"
"The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).","***FreesearchR*** opbevarer alene data i forbindelse med din analyse, men du bør kun behandle personfølsomme data når du kører ***FreesearchR*** direkte på din egen maskine. [Læs mere her](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine)."
"Quick overview","Hurtigt overblik" "Quick overview","Hurtigt overblik"
"Select variables for final import","Vælg variabler til den endelige import" "Select variables for final import","Vælg variabler til den endelige import"
"Exclude incomplete variables:","Ekskluder inkomplette variabler:" "Exclude incomplete variables:","Ekskluder inkomplette variabler:"
@ -24,16 +23,11 @@
"Apply filter on observation","Anvend filtre af observationer" "Apply filter on observation","Anvend filtre af observationer"
"Edit and create data","Ændr og opret variabler" "Edit and create data","Ændr og opret variabler"
"Subset, rename and convert variables","Udvælg, omdøb og konverter variabler" "Subset, rename and convert variables","Udvælg, omdøb og konverter variabler"
"Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.).","Nedenfor er der mulighed for at lave simple ændringer i dit datasæt, såsom at redigere variabelnavne eller beskrivelser (bedre tabeller), eller omklassificering af variabler (numerisk, factoriel/kategorisk)."
"Please note that data modifications are applied before any filtering.","Bemærk at alle ændringer i data anvendes inden filtreringen."
"Advanced data manipulation","Avanceret datamanipulation" "Advanced data manipulation","Avanceret datamanipulation"
"Below options allow more advanced varaible manipulations.","Nedenfor er mulighed for avancerede ændringer i data." "Below options allow more advanced varaible manipulations.","Nedenfor er mulighed for avancerede ændringer i data."
"New factor","Ny faktor" "New factor","Ny faktor"
"Create factor/categorical variable from a continous variable (number/date/time).","Opret kategorisk variabel på baggrund af kontinuert variabel (numerisk/dato/tid)."
"New variable","Ny variabel" "New variable","Ny variabel"
"Create a new variable based on an R-expression.","Opret ny variabel baseret på R-kode."
"Compare modified data to original","Sammenlign ændret data med det originale datasæt" "Compare modified data to original","Sammenlign ændret data med det originale datasæt"
"Raw print of the original vs the modified data.","Simpel sammenligning af det originale og det ændrede datasæt."
"Original data:","Original data:" "Original data:","Original data:"
"Modified data:","Ændret data:" "Modified data:","Ændret data:"
"New column name:","Navn til ny variabel:" "New column name:","Navn til ny variabel:"
@ -64,7 +58,6 @@
"Imported data","Importeret data" "Imported data","Importeret data"
"www/intro.md","www/intro.md" "www/intro.md","www/intro.md"
"Choose your data","Vælg dine data" "Choose your data","Vælg dine data"
"Upload a file, get data directly from REDCap or use local or sample data.","Upload en fil, hent data direkte fra en REDCap-server eller brug test-data eller lokal data."
"Factor variable to reorder:","Kategoriske variabel der skal ændres:" "Factor variable to reorder:","Kategoriske variabel der skal ændres:"
"Sort by levels","Sorter efter niveauer" "Sort by levels","Sorter efter niveauer"
"Sort by count","Sorter efter antal" "Sort by count","Sorter efter antal"
@ -95,9 +88,7 @@
"Visuals","Grafik" "Visuals","Grafik"
"Regression","Regression" "Regression","Regression"
"Download","Download" "Download","Download"
"{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.","{data_text} har {n} observationer og {n_var} variabler, med {n_complete} ({p_complete} %) komplette cases."
"Prepare","Forbered" "Prepare","Forbered"
"At 0, only complete variables are included; at 100, all variables are included.","Ved 0 inkluderes alene komplette variabler; ved 100 inkluderes alle variabler."
"The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.","De følgende variabel-par er stærkt korrelerede: {sentence_paste(.x,and_str)}.\nOvervej at fjerne en {more}fra datasættet for at sikre at prædiktorer er internt uafhængige." "The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.","De følgende variabel-par er stærkt korrelerede: {sentence_paste(.x,and_str)}.\nOvervej at fjerne en {more}fra datasættet for at sikre at prædiktorer er internt uafhængige."
"No variables have a correlation measure above the threshold.","Ingen variabler er korrelerede over den angivne tærskelværdi." "No variables have a correlation measure above the threshold.","Ingen variabler er korrelerede over den angivne tærskelværdi."
"and","og" "and","og"
@ -141,23 +132,17 @@
"Create plot","Dan grafik" "Create plot","Dan grafik"
"Coefficients plot","Koefficientgraf" "Coefficients plot","Koefficientgraf"
"Checks","Test af model" "Checks","Test af model"
"Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters.","Nedenfor er en opsummerende tabel, der giver hurtigt overblik. Til højre kan du få et visuelt overblik, gennemgå observationer og oprette datafiltre."
"Browse observations","Gennemse observationer" "Browse observations","Gennemse observationer"
"Settings","Indstillinger" "Settings","Indstillinger"
"The following error occured on determining correlations:","Følgende fejl opstod i forbindelse med korrelationsanalysen:" "The following error occured on determining correlations:","Følgende fejl opstod i forbindelse med korrelationsanalysen:"
"We encountered the following error creating your report:","Følgende fejl opstod, da rapporten blev dannet:"
"No missing observations","Ingen manglende observationer" "No missing observations","Ingen manglende observationer"
"There is a total of {p_miss} % missing observations.","Der er i alt {p_miss} % manglende observationer." "There is a total of {p_miss} % missing observations.","Der er i alt {p_miss} % manglende observationer."
"Median:","Median:" "Median:","Median:"
"Restore original data","Gendan originale data" "Restore original data","Gendan originale data"
"Reset to original imported dataset. Careful! There is no un-doing.","Gendan det oprindeligt importerede datasæt. Forsigtig! Alle dine ændringer vil forsvinde."
"Characteristics","Karakteristika" "Characteristics","Karakteristika"
"Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list.","Alene kategoriske variabler kan danne grundlag for stratificering. Mangler du en variabel, så gå til ""Forbered"" og omklassificer til kategorisk."
"Compare strata?","Sammenlign strata?" "Compare strata?","Sammenlign strata?"
"Correlations","Korrelationer" "Correlations","Korrelationer"
"To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.","For at udelukke svarvariablen fra korrelationsanalysen, så kan du vælge din svarvariabel eller vælge 'non', hvis du ikke vil angive en."
"Correlation cut-off","Korrelationsgrænse" "Correlation cut-off","Korrelationsgrænse"
"Set the cut-off for considered 'highly correlated'.","Angiv grænsen for. hvad, der tolkes som 'betydelig korrelation'."
"Missings","Manglende observationer" "Missings","Manglende observationer"
"Class","Klasse" "Class","Klasse"
"Observations","Observationer" "Observations","Observationer"
@ -167,11 +152,9 @@
"Confirm","Bekræft" "Confirm","Bekræft"
"The filtered data","Filtreret data" "The filtered data","Filtreret data"
"Create new factor","Ny kategorisk variabel" "Create new factor","Ny kategorisk variabel"
"This window is aimed at advanced users and require some *R*-experience!","Dette vindue er primært for avancerede brugere med nogen *R*-erfaring!"
"Create new variables","Opret nye variabler" "Create new variables","Opret nye variabler"
"Select data types to include","Vælg datatyper, der skal inkluderes" "Select data types to include","Vælg datatyper, der skal inkluderes"
"Uploaded data overview","Overblik over uploaded data" "Uploaded data overview","Overblik over uploaded data"
"Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias.","Her har du en oversigt over hvordan data er blevet formateret, og hvor der er manglende observationer. Brug informationen til at overveje om manglende data mangler tilfældigt eller og der er et mønster, som kan være et udtryk for systematisk manglende data (observationsbias)."
"Specify covariables","Angiv kovariabler" "Specify covariables","Angiv kovariabler"
"If none are selected, all are included.","Hvis ingen er valgt inkluderes alle." "If none are selected, all are included.","Hvis ingen er valgt inkluderes alle."
"Analyse","Analysér" "Analyse","Analysér"
@ -209,7 +192,6 @@
"List of datasets...","Liste af datasæt..." "List of datasets...","Liste af datasæt..."
"No data selected!","Ingen data valgt!" "No data selected!","Ingen data valgt!"
"No dataset here...","Ingen datasæt her..." "No dataset here...","Ingen datasæt her..."
"Use a dataset from your environment or from the environment of a package.","Brug et datasæt fra dit lokale kodemiljø eller fra en tilgængelig pakke."
"Not a data.frame","Ikke en data.frame" "Not a data.frame","Ikke en data.frame"
"Select source","Vælg datakilde" "Select source","Vælg datakilde"
"Select a data source:","Vælg datakilde:" "Select a data source:","Vælg datakilde:"
@ -229,7 +211,6 @@
"Multivariable regression model checks","Tests af multivariabel regressionsmodel" "Multivariable regression model checks","Tests af multivariabel regressionsmodel"
"Grouped by {get_label(data,ter)}","Grupperet efter {get_label(data,ter)}" "Grouped by {get_label(data,ter)}","Grupperet efter {get_label(data,ter)}"
"Option to perform statistical comparisons between strata in baseline table.","Mulighed for at udføre statistiske tests mellem strata i oversigtstabellen." "Option to perform statistical comparisons between strata in baseline table.","Mulighed for at udføre statistiske tests mellem strata i oversigtstabellen."
"Press 'Evaluate' to create the comparison table.","Tryk 'Evaluér' for at oprette en oversigtstabel."
"The data includes {n_col} variables. Please limit to 100.","Data indeholder {n_col} variabler. Begræns venligst til 100." "The data includes {n_col} variables. Please limit to 100.","Data indeholder {n_col} variabler. Begræns venligst til 100."
"Data import","Data import" "Data import","Data import"
"Data import formatting","Formatering af data ved import" "Data import formatting","Formatering af data ved import"
@ -261,7 +242,6 @@
"By specified numbers","Efter specifikke værdier" "By specified numbers","Efter specifikke værdier"
"By quantiles (groups of equal size)","I grupper af samme størrelse" "By quantiles (groups of equal size)","I grupper af samme størrelse"
"By week number","Efter ugenummer alene" "By week number","Efter ugenummer alene"
"There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data.","Der er mere avancerede muligheder for at ændre kategoriske variable, oprette nye kategoriske variabler fra eksisterende data eller nye variable baseret på R-kode. Nederst kan du gendanne originale data."
"Split the variable","Opdel variablen" "Split the variable","Opdel variablen"
"Original data","Oprindelige data" "Original data","Oprindelige data"
"Preview of result","Forhåndsvisning af resultat" "Preview of result","Forhåndsvisning af resultat"
@ -275,7 +255,6 @@
"Browse data preview","Forhåndsvisning af resultat" "Browse data preview","Forhåndsvisning af resultat"
"Split character string","Opdel tegnstreng" "Split character string","Opdel tegnstreng"
"Split text","Opdel tekst" "Split text","Opdel tekst"
"Split a text column by a recognised delimiter.","Ingen tegnvariabler med accepterede afgrænsere fundet."
"Split a character string by a common delimiter","Opdel en tekstkolonne med en fælles afgrænser" "Split a character string by a common delimiter","Opdel en tekstkolonne med en fælles afgrænser"
"Apply split","Anvend opdeling" "Apply split","Anvend opdeling"
"Stacked relative barplot","Stablet relativt søjlediagram" "Stacked relative barplot","Stablet relativt søjlediagram"
@ -290,14 +269,10 @@
"Words","Ord" "Words","Ord"
"Shorten to first letters","Afkort til første bogstaver" "Shorten to first letters","Afkort til første bogstaver"
"Shorten to first words","Afkort til de første ord" "Shorten to first words","Afkort til de første ord"
"Missings across variables by the variable **'{input$missings_var}'**","Manglende værdier på tværs af variablerne **'{input$missings_var}'**"
"Missing vs non-missing observations in the variable **'{input$missings_var}'**","Manglende vs. ikke-manglende observationer i variablen **'{input$missings_var}'**"
"Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random.","Evaluer manglende værdier ved enten at sammenligne manglende værdier på tværs af variabler (valgfrit grupperet efter en kategorisk eller dikotom variabel) eller sammenligne variabler grupperet efter manglende status (mangler eller ej) for en udfaldsvariabel. Hvis der er en signifikant forskel i manglende værdier, kan dette forårsage en bias i dine data, og det bør overvejes omhyggeligt at fortolke dataene og analyserne, da data muligvis ikke mangler tilfældigt."
"Calculating. Hold tight for a moment..","Beregner. Hold lige fast et øjeblik.." "Calculating. Hold tight for a moment..","Beregner. Hold lige fast et øjeblik.."
"Overview of missing observations","Oversigt over manglende observationer" "Overview of missing observations","Oversigt over manglende observationer"
"Analysis method for missingness overview","Analysemetode for oversigt over manglende indhold" "Analysis method for missingness overview","Analysemetode for oversigt over manglende indhold"
"Overview of missings across variables","Oversigt over mangler på tværs af variabler" "Overview of missings across variables","Oversigt over mangler på tværs af variabler"
"Overview of difference in variables by missing status in outcome","Oversigt over forskel i variabler ved manglende status i resultat"
"Select a variable for grouped overview","Vælg en variabel til grupperet oversigt" "Select a variable for grouped overview","Vælg en variabel til grupperet oversigt"
"Select outcome variable for overview","Vælg resultatvariabel for oversigt" "Select outcome variable for overview","Vælg resultatvariabel for oversigt"
"No outcome measure chosen","Ingen resultatmål valgt" "No outcome measure chosen","Ingen resultatmål valgt"
@ -341,3 +316,14 @@
"Reorder factor levels","Omarranger niveauer" "Reorder factor levels","Omarranger niveauer"
"Modify factor levels","Modify factor levels" "Modify factor levels","Modify factor levels"
"Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables." "Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables."
"Start by loading data.","Start by loading data."
"Maximum number of observations:","Maximum number of observations:"
"setting to 0 includes all","setting to 0 includes all"
"Select a dataset from your environment or sample dataset from a package.","Select a dataset from your environment or sample dataset from a package."
"Select a sample dataset from a package.","Select a sample dataset from a package."
"Data ready to be imported!","Data ready to be imported!"
"Data has %s obs. of %s variables.","Data has %s obs. of %s variables."
"Data successfully imported!","Data successfully imported!"
"Click to see data","Click to see data"
"No data present.","No data present."
"You have provided a complete dataset with no missing values.","You have provided a complete dataset with no missing values."

1 en da
5 REDCap server export Eksport fra REDCap server
6 Local or sample data Lokal eller testdata
7 Please be mindfull handling sensitive data Pas godt på og overvej nøje hvordan du håndterer personfølsomme data
The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine). ***FreesearchR*** opbevarer alene data i forbindelse med din analyse, men du bør kun behandle personfølsomme data når du kører ***FreesearchR*** direkte på din egen maskine. [Læs mere her](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).
8 Quick overview Hurtigt overblik
9 Select variables for final import Vælg variabler til den endelige import
10 Exclude incomplete variables: Ekskluder inkomplette variabler:
23 Apply filter on observation Anvend filtre af observationer
24 Edit and create data Ændr og opret variabler
25 Subset, rename and convert variables Udvælg, omdøb og konverter variabler
Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.). Nedenfor er der mulighed for at lave simple ændringer i dit datasæt, såsom at redigere variabelnavne eller beskrivelser (bedre tabeller), eller omklassificering af variabler (numerisk, factoriel/kategorisk).
Please note that data modifications are applied before any filtering. Bemærk at alle ændringer i data anvendes inden filtreringen.
26 Advanced data manipulation Avanceret datamanipulation
27 Below options allow more advanced varaible manipulations. Nedenfor er mulighed for avancerede ændringer i data.
28 New factor Ny faktor
Create factor/categorical variable from a continous variable (number/date/time). Opret kategorisk variabel på baggrund af kontinuert variabel (numerisk/dato/tid).
29 New variable Ny variabel
Create a new variable based on an R-expression. Opret ny variabel baseret på R-kode.
30 Compare modified data to original Sammenlign ændret data med det originale datasæt
Raw print of the original vs the modified data. Simpel sammenligning af det originale og det ændrede datasæt.
31 Original data: Original data:
32 Modified data: Ændret data:
33 New column name: Navn til ny variabel:
58 Imported data Importeret data
59 www/intro.md www/intro.md
60 Choose your data Vælg dine data
Upload a file, get data directly from REDCap or use local or sample data. Upload en fil, hent data direkte fra en REDCap-server eller brug test-data eller lokal data.
61 Factor variable to reorder: Kategoriske variabel der skal ændres:
62 Sort by levels Sorter efter niveauer
63 Sort by count Sorter efter antal
88 Visuals Grafik
89 Regression Regression
90 Download Download
{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases. {data_text} har {n} observationer og {n_var} variabler, med {n_complete} ({p_complete} %) komplette cases.
91 Prepare Forbered
At 0, only complete variables are included; at 100, all variables are included. Ved 0 inkluderes alene komplette variabler; ved 100 inkluderes alle variabler.
92 The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent. De følgende variabel-par er stærkt korrelerede: {sentence_paste(.x,and_str)}.\nOvervej at fjerne en {more}fra datasættet for at sikre at prædiktorer er internt uafhængige.
93 No variables have a correlation measure above the threshold. Ingen variabler er korrelerede over den angivne tærskelværdi.
94 and og
132 Create plot Dan grafik
133 Coefficients plot Koefficientgraf
134 Checks Test af model
Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters. Nedenfor er en opsummerende tabel, der giver hurtigt overblik. Til højre kan du få et visuelt overblik, gennemgå observationer og oprette datafiltre.
135 Browse observations Gennemse observationer
136 Settings Indstillinger
137 The following error occured on determining correlations: Følgende fejl opstod i forbindelse med korrelationsanalysen:
We encountered the following error creating your report: Følgende fejl opstod, da rapporten blev dannet:
138 No missing observations Ingen manglende observationer
139 There is a total of {p_miss} % missing observations. Der er i alt {p_miss} % manglende observationer.
140 Median: Median:
141 Restore original data Gendan originale data
Reset to original imported dataset. Careful! There is no un-doing. Gendan det oprindeligt importerede datasæt. Forsigtig! Alle dine ændringer vil forsvinde.
142 Characteristics Karakteristika
Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list. Alene kategoriske variabler kan danne grundlag for stratificering. Mangler du en variabel, så gå til "Forbered" og omklassificer til kategorisk.
143 Compare strata? Sammenlign strata?
144 Correlations Korrelationer
To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'. For at udelukke svarvariablen fra korrelationsanalysen, så kan du vælge din svarvariabel eller vælge 'non', hvis du ikke vil angive en.
145 Correlation cut-off Korrelationsgrænse
Set the cut-off for considered 'highly correlated'. Angiv grænsen for. hvad, der tolkes som 'betydelig korrelation'.
146 Missings Manglende observationer
147 Class Klasse
148 Observations Observationer
152 Confirm Bekræft
153 The filtered data Filtreret data
154 Create new factor Ny kategorisk variabel
This window is aimed at advanced users and require some *R*-experience! Dette vindue er primært for avancerede brugere med nogen *R*-erfaring!
155 Create new variables Opret nye variabler
156 Select data types to include Vælg datatyper, der skal inkluderes
157 Uploaded data overview Overblik over uploaded data
Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias. Her har du en oversigt over hvordan data er blevet formateret, og hvor der er manglende observationer. Brug informationen til at overveje om manglende data mangler tilfældigt eller og der er et mønster, som kan være et udtryk for systematisk manglende data (observationsbias).
158 Specify covariables Angiv kovariabler
159 If none are selected, all are included. Hvis ingen er valgt inkluderes alle.
160 Analyse Analysér
192 List of datasets... Liste af datasæt...
193 No data selected! Ingen data valgt!
194 No dataset here... Ingen datasæt her...
Use a dataset from your environment or from the environment of a package. Brug et datasæt fra dit lokale kodemiljø eller fra en tilgængelig pakke.
195 Not a data.frame Ikke en data.frame
196 Select source Vælg datakilde
197 Select a data source: Vælg datakilde:
211 Multivariable regression model checks Tests af multivariabel regressionsmodel
212 Grouped by {get_label(data,ter)} Grupperet efter {get_label(data,ter)}
213 Option to perform statistical comparisons between strata in baseline table. Mulighed for at udføre statistiske tests mellem strata i oversigtstabellen.
Press 'Evaluate' to create the comparison table. Tryk 'Evaluér' for at oprette en oversigtstabel.
214 The data includes {n_col} variables. Please limit to 100. Data indeholder {n_col} variabler. Begræns venligst til 100.
215 Data import Data import
216 Data import formatting Formatering af data ved import
242 By specified numbers Efter specifikke værdier
243 By quantiles (groups of equal size) I grupper af samme størrelse
244 By week number Efter ugenummer alene
There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data. Der er mere avancerede muligheder for at ændre kategoriske variable, oprette nye kategoriske variabler fra eksisterende data eller nye variable baseret på R-kode. Nederst kan du gendanne originale data.
245 Split the variable Opdel variablen
246 Original data Oprindelige data
247 Preview of result Forhåndsvisning af resultat
255 Browse data preview Forhåndsvisning af resultat
256 Split character string Opdel tegnstreng
257 Split text Opdel tekst
Split a text column by a recognised delimiter. Ingen tegnvariabler med accepterede afgrænsere fundet.
258 Split a character string by a common delimiter Opdel en tekstkolonne med en fælles afgrænser
259 Apply split Anvend opdeling
260 Stacked relative barplot Stablet relativt søjlediagram
269 Words Ord
270 Shorten to first letters Afkort til første bogstaver
271 Shorten to first words Afkort til de første ord
Missings across variables by the variable **'{input$missings_var}'** Manglende værdier på tværs af variablerne **'{input$missings_var}'**
Missing vs non-missing observations in the variable **'{input$missings_var}'** Manglende vs. ikke-manglende observationer i variablen **'{input$missings_var}'**
Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random. Evaluer manglende værdier ved enten at sammenligne manglende værdier på tværs af variabler (valgfrit grupperet efter en kategorisk eller dikotom variabel) eller sammenligne variabler grupperet efter manglende status (mangler eller ej) for en udfaldsvariabel. Hvis der er en signifikant forskel i manglende værdier, kan dette forårsage en bias i dine data, og det bør overvejes omhyggeligt at fortolke dataene og analyserne, da data muligvis ikke mangler tilfældigt.
272 Calculating. Hold tight for a moment.. Beregner. Hold lige fast et øjeblik..
273 Overview of missing observations Oversigt over manglende observationer
274 Analysis method for missingness overview Analysemetode for oversigt over manglende indhold
275 Overview of missings across variables Oversigt over mangler på tværs af variabler
Overview of difference in variables by missing status in outcome Oversigt over forskel i variabler ved manglende status i resultat
276 Select a variable for grouped overview Vælg en variabel til grupperet oversigt
277 Select outcome variable for overview Vælg resultatvariabel for oversigt
278 No outcome measure chosen Ingen resultatmål valgt
316 Reorder factor levels Omarranger niveauer
317 Modify factor levels Modify factor levels
318 Reorder or rename the levels of factor/categorical variables. Reorder or rename the levels of factor/categorical variables.
319 Start by loading data. Start by loading data.
320 Maximum number of observations: Maximum number of observations:
321 setting to 0 includes all setting to 0 includes all
322 Select a dataset from your environment or sample dataset from a package. Select a dataset from your environment or sample dataset from a package.
323 Select a sample dataset from a package. Select a sample dataset from a package.
324 Data ready to be imported! Data ready to be imported!
325 Data has %s obs. of %s variables. Data has %s obs. of %s variables.
326 Data successfully imported! Data successfully imported!
327 Click to see data Click to see data
328 No data present. No data present.
329 You have provided a complete dataset with no missing values. You have provided a complete dataset with no missing values.

36
inst/translations/translation_sw.csv
View file

@ -5,7 +5,6 @@
"REDCap server export","Usafirishaji wa seva ya REDCap" "REDCap server export","Usafirishaji wa seva ya REDCap"
"Local or sample data","Data ya ndani au ya sampuli" "Local or sample data","Data ya ndani au ya sampuli"
"Please be mindfull handling sensitive data","Tafadhali kuwa mwangalifu kushughulikia data nyeti" "Please be mindfull handling sensitive data","Tafadhali kuwa mwangalifu kushughulikia data nyeti"
"The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).","Programu ya ***FreesearchR*** huhifadhi data kwa ajili ya uchambuzi pekee, lakini tafadhali tumia tu na data nyeti unapoendesha ndani. [Soma zaidi hapa](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine)."
"Quick overview","Muhtasari wa haraka" "Quick overview","Muhtasari wa haraka"
"Select variables for final import","Chagua vigezo vya kuingiza mwisho" "Select variables for final import","Chagua vigezo vya kuingiza mwisho"
"Exclude incomplete variables:","Ondoa vigezo visivyokamilika:" "Exclude incomplete variables:","Ondoa vigezo visivyokamilika:"
@ -24,16 +23,11 @@
"Apply filter on observation","Tumia kichujio wakati wa uchunguzi" "Apply filter on observation","Tumia kichujio wakati wa uchunguzi"
"Edit and create data","Hariri na uunde data" "Edit and create data","Hariri na uunde data"
"Subset, rename and convert variables","Weka sehemu ndogo, badilisha jina na ubadilishe vigezo" "Subset, rename and convert variables","Weka sehemu ndogo, badilisha jina na ubadilishe vigezo"
"Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.).","Hapa chini, kuna chaguo kadhaa za urekebishaji rahisi wa data kama vile kusasisha vigezo kwa kubadilisha majina, kuunda lebo mpya (kwa majedwali mazuri zaidi katika ripoti) na kubadilisha madarasa ya vigezo (nambari, vipengele/kategoria n.k.)."
"Please note that data modifications are applied before any filtering.","Tafadhali kumbuka kwamba marekebisho ya data hutumika kabla ya kuchuja yoyote."
"Advanced data manipulation","Udhibiti wa data wa hali ya juu" "Advanced data manipulation","Udhibiti wa data wa hali ya juu"
"Below options allow more advanced varaible manipulations.","Chaguzi zilizo hapa chini huruhusu udanganyifu wa hali ya juu zaidi unaoweza kubadilika." "Below options allow more advanced varaible manipulations.","Chaguzi zilizo hapa chini huruhusu udanganyifu wa hali ya juu zaidi unaoweza kubadilika."
"New factor","Kipengele kipya" "New factor","Kipengele kipya"
"Create factor/categorical variable from a continous variable (number/date/time).","Unda kigezo cha kipengele/kitengo kutoka kwa kigezo endelevu (nambari/tarehe/saa)."
"New variable","Kigezo kipya" "New variable","Kigezo kipya"
"Create a new variable based on an R-expression.","Unda kigezo kipya kulingana na usemi wa R."
"Compare modified data to original","Linganisha data iliyobadilishwa na ya asili" "Compare modified data to original","Linganisha data iliyobadilishwa na ya asili"
"Raw print of the original vs the modified data.","Chapisho ghafi la data asili dhidi ya data iliyorekebishwa."
"Original data:","Data asilia:" "Original data:","Data asilia:"
"Modified data:","Data iliyorekebishwa:" "Modified data:","Data iliyorekebishwa:"
"New column name:","Jina jipya la safu wima:" "New column name:","Jina jipya la safu wima:"
@ -64,7 +58,6 @@
"Imported data","Data iliyoingizwa" "Imported data","Data iliyoingizwa"
"www/intro.md","www/intro.md" "www/intro.md","www/intro.md"
"Choose your data","Chagua data yako" "Choose your data","Chagua data yako"
"Upload a file, get data directly from REDCap or use local or sample data.","Pakia faili, pata data moja kwa moja kutoka REDCap au tumia data ya ndani au sampuli."
"Factor variable to reorder:","Kigezo cha vipengele ili kupanga upya:" "Factor variable to reorder:","Kigezo cha vipengele ili kupanga upya:"
"Sort by levels","Panga kwa viwango" "Sort by levels","Panga kwa viwango"
"Sort by count","Panga kwa hesabu" "Sort by count","Panga kwa hesabu"
@ -95,9 +88,7 @@
"Visuals","Picha" "Visuals","Picha"
"Regression","Urejeshaji" "Regression","Urejeshaji"
"Download","Pakua" "Download","Pakua"
"{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.","{data_text} ina uchunguzi wa {n} na vigezo vya {n_var}, pamoja na visa kamili vya {n_complete} ({p_complete}%)."
"Prepare","Tayarisha" "Prepare","Tayarisha"
"At 0, only complete variables are included; at 100, all variables are included.","Katika 0, ni vigezo kamili pekee vilivyojumuishwa; katika 100, vigezo vyote vimejumuishwa."
"The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.","Jozi zifuatazo za vigeu zina uhusiano wa hali ya juu: {sentence_paste(.x,and_str)}.\nFikiria kutenga moja {zaidi} kutoka kwenye seti ya data ili kuhakikisha vigeu vinajitegemea." "The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.","Jozi zifuatazo za vigeu zina uhusiano wa hali ya juu: {sentence_paste(.x,and_str)}.\nFikiria kutenga moja {zaidi} kutoka kwenye seti ya data ili kuhakikisha vigeu vinajitegemea."
"No variables have a correlation measure above the threshold.","Hakuna vigezo vyenye kipimo cha uhusiano kilicho juu ya kizingiti." "No variables have a correlation measure above the threshold.","Hakuna vigezo vyenye kipimo cha uhusiano kilicho juu ya kizingiti."
"and","na" "and","na"
@ -141,23 +132,17 @@
"Create plot","Unda njama" "Create plot","Unda njama"
"Coefficients plot","Mchoro wa viambato" "Coefficients plot","Mchoro wa viambato"
"Checks","Hundi" "Checks","Hundi"
"Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters.","Hapa chini kuna jedwali la muhtasari kwa ajili ya ufahamu wa haraka, na upande wa kulia unaweza kuibua madarasa ya data, kuvinjari uchunguzi na kutumia vichujio tofauti vya data."
"Browse observations","Vinjari uchunguzi" "Browse observations","Vinjari uchunguzi"
"Settings","Mipangilio" "Settings","Mipangilio"
"The following error occured on determining correlations:","Hitilafu ifuatayo ilitokea katika kubaini uhusiano:" "The following error occured on determining correlations:","Hitilafu ifuatayo ilitokea katika kubaini uhusiano:"
"We encountered the following error creating your report:","Tulikutana na hitilafu ifuatayo katika kuunda ripoti yako:"
"No missing observations","Hakuna uchunguzi unaokosekana" "No missing observations","Hakuna uchunguzi unaokosekana"
"There is a total of {p_miss} % missing observations.","Kuna jumla ya uchunguzi wa {p_miss}% unaokosekana." "There is a total of {p_miss} % missing observations.","Kuna jumla ya uchunguzi wa {p_miss}% unaokosekana."
"Median:","Wastani:" "Median:","Wastani:"
"Restore original data","Rejesha data asili" "Restore original data","Rejesha data asili"
"Reset to original imported dataset. Careful! There is no un-doing.","Rudisha kwenye seti ya data asili iliyoingizwa. Kuwa mwangalifu! Hakuna kutengua."
"Characteristics","Sifa" "Characteristics","Sifa"
"Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list.","Vigezo vya vipengele/kategoria pekee ndivyo vinavyopatikana kwa ajili ya uainishaji wa tabaka. Rudi kwenye kichupo cha 'Tayarisha' ili kupanga upya kigezo ikiwa hakipo kwenye orodha."
"Compare strata?","Linganisha tabaka?" "Compare strata?","Linganisha tabaka?"
"Correlations","Uhusiano" "Correlations","Uhusiano"
"To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.","Ili kuepuka kutathmini uhusiano wa kigezo cha matokeo, hii inaweza kutengwa kwenye njama au kuchagua 'hakuna'."
"Correlation cut-off","Kikomo cha uhusiano" "Correlation cut-off","Kikomo cha uhusiano"
"Set the cut-off for considered 'highly correlated'.","Weka kikomo cha 'kinachohusiana sana'."
"Missings","Hazipo" "Missings","Hazipo"
"Class","Darasa" "Class","Darasa"
"Observations","Uchunguzi" "Observations","Uchunguzi"
@ -167,11 +152,9 @@
"Confirm","Thibitisha" "Confirm","Thibitisha"
"The filtered data","Data iliyochujwa" "The filtered data","Data iliyochujwa"
"Create new factor","Unda kipengele kipya" "Create new factor","Unda kipengele kipya"
"This window is aimed at advanced users and require some *R*-experience!","Dirisha hili linalenga watumiaji wa hali ya juu na linahitaji uzoefu wa *R*!"
"Create new variables","Unda vigezo vipya" "Create new variables","Unda vigezo vipya"
"Select data types to include","Chagua aina za data za kujumuisha" "Select data types to include","Chagua aina za data za kujumuisha"
"Uploaded data overview","Muhtasari wa data iliyopakiwa" "Uploaded data overview","Muhtasari wa data iliyopakiwa"
"Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias.","Hapa kuna muhtasari wa jinsi data yako inavyotafsiriwa, na mahali ambapo data inakosekana. Tumia taarifa hii kuzingatia ikiwa data inakosekana bila mpangilio au ikiwa baadhi ya uchunguzi unakosekana kimfumo ambao unaweza kusababishwa na upendeleo wa uchunguzi."
"Specify covariables","Bainisha vigeu vinavyoweza kuunganishwa" "Specify covariables","Bainisha vigeu vinavyoweza kuunganishwa"
"If none are selected, all are included.","Ikiwa hakuna aliyechaguliwa, wote wamejumuishwa." "If none are selected, all are included.","Ikiwa hakuna aliyechaguliwa, wote wamejumuishwa."
"Analyse","Changanua" "Analyse","Changanua"
@ -209,7 +192,6 @@
"List of datasets...","Orodha ya seti za data..." "List of datasets...","Orodha ya seti za data..."
"No data selected!","Hakuna data iliyochaguliwa!" "No data selected!","Hakuna data iliyochaguliwa!"
"No dataset here...","Hakuna seti ya data hapa..." "No dataset here...","Hakuna seti ya data hapa..."
"Use a dataset from your environment or from the environment of a package.","Tumia seti ya data kutoka kwa mazingira yako au kutoka kwa mazingira ya kifurushi."
"Not a data.frame","Sio data.frame" "Not a data.frame","Sio data.frame"
"Select source","Chagua chanzo" "Select source","Chagua chanzo"
"Select a data source:","Chagua chanzo cha data:" "Select a data source:","Chagua chanzo cha data:"
@ -229,7 +211,6 @@
"Multivariable regression model checks","Ukaguzi wa modeli ya urejeshaji unaoweza kubadilika-badilika" "Multivariable regression model checks","Ukaguzi wa modeli ya urejeshaji unaoweza kubadilika-badilika"
"Grouped by {get_label(data,ter)}","Imepangwa kwa makundi kulingana na {get_label(data,ter)}" "Grouped by {get_label(data,ter)}","Imepangwa kwa makundi kulingana na {get_label(data,ter)}"
"Option to perform statistical comparisons between strata in baseline table.","Chaguo la kufanya ulinganisho wa takwimu kati ya tabaka katika jedwali la msingi." "Option to perform statistical comparisons between strata in baseline table.","Chaguo la kufanya ulinganisho wa takwimu kati ya tabaka katika jedwali la msingi."
"Press 'Evaluate' to create the comparison table.","Bonyeza 'Tathmini' ili kuunda jedwali la kulinganisha."
"The data includes {n_col} variables. Please limit to 100.","Data inajumuisha vigezo vya {n_col}. Tafadhali punguza hadi 100." "The data includes {n_col} variables. Please limit to 100.","Data inajumuisha vigezo vya {n_col}. Tafadhali punguza hadi 100."
"Data import","Uingizaji wa data" "Data import","Uingizaji wa data"
"Data import formatting","Uumbizaji wa kuingiza data" "Data import formatting","Uumbizaji wa kuingiza data"
@ -261,7 +242,6 @@
"By specified numbers","Kwa nambari zilizoainishwa" "By specified numbers","Kwa nambari zilizoainishwa"
"By quantiles (groups of equal size)","Kwa quantiles (vikundi vya ukubwa sawa)" "By quantiles (groups of equal size)","Kwa quantiles (vikundi vya ukubwa sawa)"
"Please fill in web address and API token, then press 'Connect'.","Tafadhali jaza anwani ya wavuti na tokeni ya API, kisha bonyeza 'Unganisha'." "Please fill in web address and API token, then press 'Connect'.","Tafadhali jaza anwani ya wavuti na tokeni ya API, kisha bonyeza 'Unganisha'."
"There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data.","Kuna chaguo za hali ya juu zaidi za kurekebisha vigezo vya vipengele/kategoria pamoja na kuunda kipengele kipya kutoka kwa kigezo kilichopo au vigezo vipya vyenye msimbo wa R. Chini unaweza kurejesha data asili."
"Text or character to split string by","Maandishi au herufi ya kugawanya mfuatano kwa" "Text or character to split string by","Maandishi au herufi ya kugawanya mfuatano kwa"
"Split the variable","Gawanya kigezo" "Split the variable","Gawanya kigezo"
"Variable to split:","Kinachoweza kubadilika hadi kugawanyika:" "Variable to split:","Kinachoweza kubadilika hadi kugawanyika:"
@ -276,7 +256,6 @@
"Original data","Data asili" "Original data","Data asili"
"Preview of result","Hakikisho la matokeo" "Preview of result","Hakikisho la matokeo"
"No character variables with accepted delimiters detected.","Hakuna vigezo vya herufi vilivyo na vidhibiti vinavyokubalika vilivyogunduliwa." "No character variables with accepted delimiters detected.","Hakuna vigezo vya herufi vilivyo na vidhibiti vinavyokubalika vilivyogunduliwa."
"Split a text column by a recognised delimiter.","Gawanya safu wima ya maandishi kwa kitenga kinachotambulika."
"Apply split","Tumia mgawanyiko" "Apply split","Tumia mgawanyiko"
"Stacked relative barplot","Kipande cha baruni kilichopangwa kwa mirundiko" "Stacked relative barplot","Kipande cha baruni kilichopangwa kwa mirundiko"
"Create relative stacked barplots to show the distribution of categorical levels","Unda viwanja vya baruni vilivyopangwa ili kuonyesha usambazaji wa viwango vya kategoria" "Create relative stacked barplots to show the distribution of categorical levels","Unda viwanja vya baruni vilivyopangwa ili kuonyesha usambazaji wa viwango vya kategoria"
@ -290,14 +269,10 @@
"Words","Maneno" "Words","Maneno"
"Shorten to first letters","Fupisha herufi za kwanza" "Shorten to first letters","Fupisha herufi za kwanza"
"Shorten to first words","Fupisha maneno ya kwanza" "Shorten to first words","Fupisha maneno ya kwanza"
"Missings across variables by the variable **'{input$missings_var}'**","Hazipo katika vigezo kwa kigezo **'{input$missings_var}'**"
"Missing vs non-missing observations in the variable **'{input$missings_var}'**","Uchunguzi unaokosekana dhidi ya usiokosekana katika kigezo **'{input$missings_var}'**"
"Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random.","Tathmini upungufu kwa kulinganisha thamani zinazokosekana katika vigezo (hiari zilizopangwa kwa mujibu wa kigezo cha kategoria au cha pande mbili) au linganisha vigezo vilivyopangwa kwa mujibu wa hali inayokosekana (inayokosekana au isiyokosekana) ya kigezo cha matokeo. Ikiwa kuna tofauti kubwa katika upungufu, hii inaweza kusababisha upendeleo katika data yako na inapaswa kuzingatiwa kwa uangalifu kutafsiri data na uchambuzi kwani data inaweza isikosekane bila mpangilio."
"Calculating. Hold tight for a moment..","Kuhesabu. Shikilia kwa muda.." "Calculating. Hold tight for a moment..","Kuhesabu. Shikilia kwa muda.."
"Overview of missing observations","Muhtasari wa uchunguzi uliokosekana" "Overview of missing observations","Muhtasari wa uchunguzi uliokosekana"
"Analysis method for missingness overview","Mbinu ya uchambuzi wa muhtasari wa kukosekana" "Analysis method for missingness overview","Mbinu ya uchambuzi wa muhtasari wa kukosekana"
"Overview of missings across variables","Muhtasari wa mambo yanayokosekana katika vigezo" "Overview of missings across variables","Muhtasari wa mambo yanayokosekana katika vigezo"
"Overview of difference in variables by missing status in outcome","Muhtasari wa tofauti katika vigezo kwa kukosa hali katika matokeo"
"Select a variable for grouped overview","Chagua kigezo cha muhtasari wa kikundi" "Select a variable for grouped overview","Chagua kigezo cha muhtasari wa kikundi"
"Select outcome variable for overview","Chagua kigezo cha matokeo kwa muhtasari" "Select outcome variable for overview","Chagua kigezo cha matokeo kwa muhtasari"
"No outcome measure chosen","Hakuna kipimo cha matokeo kilichochaguliwa" "No outcome measure chosen","Hakuna kipimo cha matokeo kilichochaguliwa"
@ -341,3 +316,14 @@
"Reorder factor levels","Reorder factor levels" "Reorder factor levels","Reorder factor levels"
"Modify factor levels","Modify factor levels" "Modify factor levels","Modify factor levels"
"Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables." "Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables."
"Start by loading data.","Start by loading data."
"Maximum number of observations:","Maximum number of observations:"
"setting to 0 includes all","setting to 0 includes all"
"Select a dataset from your environment or sample dataset from a package.","Select a dataset from your environment or sample dataset from a package."
"Select a sample dataset from a package.","Select a sample dataset from a package."
"Data ready to be imported!","Data ready to be imported!"
"Data has %s obs. of %s variables.","Data has %s obs. of %s variables."
"Data successfully imported!","Data successfully imported!"
"Click to see data","Click to see data"
"No data present.","No data present."
"You have provided a complete dataset with no missing values.","You have provided a complete dataset with no missing values."

1 en sw
5 REDCap server export Usafirishaji wa seva ya REDCap
6 Local or sample data Data ya ndani au ya sampuli
7 Please be mindfull handling sensitive data Tafadhali kuwa mwangalifu kushughulikia data nyeti
The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine). Programu ya ***FreesearchR*** huhifadhi data kwa ajili ya uchambuzi pekee, lakini tafadhali tumia tu na data nyeti unapoendesha ndani. [Soma zaidi hapa](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).
8 Quick overview Muhtasari wa haraka
9 Select variables for final import Chagua vigezo vya kuingiza mwisho
10 Exclude incomplete variables: Ondoa vigezo visivyokamilika:
23 Apply filter on observation Tumia kichujio wakati wa uchunguzi
24 Edit and create data Hariri na uunde data
25 Subset, rename and convert variables Weka sehemu ndogo, badilisha jina na ubadilishe vigezo
Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.). Hapa chini, kuna chaguo kadhaa za urekebishaji rahisi wa data kama vile kusasisha vigezo kwa kubadilisha majina, kuunda lebo mpya (kwa majedwali mazuri zaidi katika ripoti) na kubadilisha madarasa ya vigezo (nambari, vipengele/kategoria n.k.).
Please note that data modifications are applied before any filtering. Tafadhali kumbuka kwamba marekebisho ya data hutumika kabla ya kuchuja yoyote.
26 Advanced data manipulation Udhibiti wa data wa hali ya juu
27 Below options allow more advanced varaible manipulations. Chaguzi zilizo hapa chini huruhusu udanganyifu wa hali ya juu zaidi unaoweza kubadilika.
28 New factor Kipengele kipya
Create factor/categorical variable from a continous variable (number/date/time). Unda kigezo cha kipengele/kitengo kutoka kwa kigezo endelevu (nambari/tarehe/saa).
29 New variable Kigezo kipya
Create a new variable based on an R-expression. Unda kigezo kipya kulingana na usemi wa R.
30 Compare modified data to original Linganisha data iliyobadilishwa na ya asili
Raw print of the original vs the modified data. Chapisho ghafi la data asili dhidi ya data iliyorekebishwa.
31 Original data: Data asilia:
32 Modified data: Data iliyorekebishwa:
33 New column name: Jina jipya la safu wima:
58 Imported data Data iliyoingizwa
59 www/intro.md www/intro.md
60 Choose your data Chagua data yako
Upload a file, get data directly from REDCap or use local or sample data. Pakia faili, pata data moja kwa moja kutoka REDCap au tumia data ya ndani au sampuli.
61 Factor variable to reorder: Kigezo cha vipengele ili kupanga upya:
62 Sort by levels Panga kwa viwango
63 Sort by count Panga kwa hesabu
88 Visuals Picha
89 Regression Urejeshaji
90 Download Pakua
{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases. {data_text} ina uchunguzi wa {n} na vigezo vya {n_var}, pamoja na visa kamili vya {n_complete} ({p_complete}%).
91 Prepare Tayarisha
At 0, only complete variables are included; at 100, all variables are included. Katika 0, ni vigezo kamili pekee vilivyojumuishwa; katika 100, vigezo vyote vimejumuishwa.
92 The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent. Jozi zifuatazo za vigeu zina uhusiano wa hali ya juu: {sentence_paste(.x,and_str)}.\nFikiria kutenga moja {zaidi} kutoka kwenye seti ya data ili kuhakikisha vigeu vinajitegemea.
93 No variables have a correlation measure above the threshold. Hakuna vigezo vyenye kipimo cha uhusiano kilicho juu ya kizingiti.
94 and na
132 Create plot Unda njama
133 Coefficients plot Mchoro wa viambato
134 Checks Hundi
Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters. Hapa chini kuna jedwali la muhtasari kwa ajili ya ufahamu wa haraka, na upande wa kulia unaweza kuibua madarasa ya data, kuvinjari uchunguzi na kutumia vichujio tofauti vya data.
135 Browse observations Vinjari uchunguzi
136 Settings Mipangilio
137 The following error occured on determining correlations: Hitilafu ifuatayo ilitokea katika kubaini uhusiano:
We encountered the following error creating your report: Tulikutana na hitilafu ifuatayo katika kuunda ripoti yako:
138 No missing observations Hakuna uchunguzi unaokosekana
139 There is a total of {p_miss} % missing observations. Kuna jumla ya uchunguzi wa {p_miss}% unaokosekana.
140 Median: Wastani:
141 Restore original data Rejesha data asili
Reset to original imported dataset. Careful! There is no un-doing. Rudisha kwenye seti ya data asili iliyoingizwa. Kuwa mwangalifu! Hakuna kutengua.
142 Characteristics Sifa
Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list. Vigezo vya vipengele/kategoria pekee ndivyo vinavyopatikana kwa ajili ya uainishaji wa tabaka. Rudi kwenye kichupo cha 'Tayarisha' ili kupanga upya kigezo ikiwa hakipo kwenye orodha.
143 Compare strata? Linganisha tabaka?
144 Correlations Uhusiano
To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'. Ili kuepuka kutathmini uhusiano wa kigezo cha matokeo, hii inaweza kutengwa kwenye njama au kuchagua 'hakuna'.
145 Correlation cut-off Kikomo cha uhusiano
Set the cut-off for considered 'highly correlated'. Weka kikomo cha 'kinachohusiana sana'.
146 Missings Hazipo
147 Class Darasa
148 Observations Uchunguzi
152 Confirm Thibitisha
153 The filtered data Data iliyochujwa
154 Create new factor Unda kipengele kipya
This window is aimed at advanced users and require some *R*-experience! Dirisha hili linalenga watumiaji wa hali ya juu na linahitaji uzoefu wa *R*!
155 Create new variables Unda vigezo vipya
156 Select data types to include Chagua aina za data za kujumuisha
157 Uploaded data overview Muhtasari wa data iliyopakiwa
Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias. Hapa kuna muhtasari wa jinsi data yako inavyotafsiriwa, na mahali ambapo data inakosekana. Tumia taarifa hii kuzingatia ikiwa data inakosekana bila mpangilio au ikiwa baadhi ya uchunguzi unakosekana kimfumo ambao unaweza kusababishwa na upendeleo wa uchunguzi.
158 Specify covariables Bainisha vigeu vinavyoweza kuunganishwa
159 If none are selected, all are included. Ikiwa hakuna aliyechaguliwa, wote wamejumuishwa.
160 Analyse Changanua
192 List of datasets... Orodha ya seti za data...
193 No data selected! Hakuna data iliyochaguliwa!
194 No dataset here... Hakuna seti ya data hapa...
Use a dataset from your environment or from the environment of a package. Tumia seti ya data kutoka kwa mazingira yako au kutoka kwa mazingira ya kifurushi.
195 Not a data.frame Sio data.frame
196 Select source Chagua chanzo
197 Select a data source: Chagua chanzo cha data:
211 Multivariable regression model checks Ukaguzi wa modeli ya urejeshaji unaoweza kubadilika-badilika
212 Grouped by {get_label(data,ter)} Imepangwa kwa makundi kulingana na {get_label(data,ter)}
213 Option to perform statistical comparisons between strata in baseline table. Chaguo la kufanya ulinganisho wa takwimu kati ya tabaka katika jedwali la msingi.
Press 'Evaluate' to create the comparison table. Bonyeza 'Tathmini' ili kuunda jedwali la kulinganisha.
214 The data includes {n_col} variables. Please limit to 100. Data inajumuisha vigezo vya {n_col}. Tafadhali punguza hadi 100.
215 Data import Uingizaji wa data
216 Data import formatting Uumbizaji wa kuingiza data
242 By specified numbers Kwa nambari zilizoainishwa
243 By quantiles (groups of equal size) Kwa quantiles (vikundi vya ukubwa sawa)
244 Please fill in web address and API token, then press 'Connect'. Tafadhali jaza anwani ya wavuti na tokeni ya API, kisha bonyeza 'Unganisha'.
There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data. Kuna chaguo za hali ya juu zaidi za kurekebisha vigezo vya vipengele/kategoria pamoja na kuunda kipengele kipya kutoka kwa kigezo kilichopo au vigezo vipya vyenye msimbo wa R. Chini unaweza kurejesha data asili.
245 Text or character to split string by Maandishi au herufi ya kugawanya mfuatano kwa
246 Split the variable Gawanya kigezo
247 Variable to split: Kinachoweza kubadilika hadi kugawanyika:
256 Original data Data asili
257 Preview of result Hakikisho la matokeo
258 No character variables with accepted delimiters detected. Hakuna vigezo vya herufi vilivyo na vidhibiti vinavyokubalika vilivyogunduliwa.
Split a text column by a recognised delimiter. Gawanya safu wima ya maandishi kwa kitenga kinachotambulika.
259 Apply split Tumia mgawanyiko
260 Stacked relative barplot Kipande cha baruni kilichopangwa kwa mirundiko
261 Create relative stacked barplots to show the distribution of categorical levels Unda viwanja vya baruni vilivyopangwa ili kuonyesha usambazaji wa viwango vya kategoria
269 Words Maneno
270 Shorten to first letters Fupisha herufi za kwanza
271 Shorten to first words Fupisha maneno ya kwanza
Missings across variables by the variable **'{input$missings_var}'** Hazipo katika vigezo kwa kigezo **'{input$missings_var}'**
Missing vs non-missing observations in the variable **'{input$missings_var}'** Uchunguzi unaokosekana dhidi ya usiokosekana katika kigezo **'{input$missings_var}'**
Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random. Tathmini upungufu kwa kulinganisha thamani zinazokosekana katika vigezo (hiari zilizopangwa kwa mujibu wa kigezo cha kategoria au cha pande mbili) au linganisha vigezo vilivyopangwa kwa mujibu wa hali inayokosekana (inayokosekana au isiyokosekana) ya kigezo cha matokeo. Ikiwa kuna tofauti kubwa katika upungufu, hii inaweza kusababisha upendeleo katika data yako na inapaswa kuzingatiwa kwa uangalifu kutafsiri data na uchambuzi kwani data inaweza isikosekane bila mpangilio.
272 Calculating. Hold tight for a moment.. Kuhesabu. Shikilia kwa muda..
273 Overview of missing observations Muhtasari wa uchunguzi uliokosekana
274 Analysis method for missingness overview Mbinu ya uchambuzi wa muhtasari wa kukosekana
275 Overview of missings across variables Muhtasari wa mambo yanayokosekana katika vigezo
Overview of difference in variables by missing status in outcome Muhtasari wa tofauti katika vigezo kwa kukosa hali katika matokeo
276 Select a variable for grouped overview Chagua kigezo cha muhtasari wa kikundi
277 Select outcome variable for overview Chagua kigezo cha matokeo kwa muhtasari
278 No outcome measure chosen Hakuna kipimo cha matokeo kilichochaguliwa
316 Reorder factor levels Reorder factor levels
317 Modify factor levels Modify factor levels
318 Reorder or rename the levels of factor/categorical variables. Reorder or rename the levels of factor/categorical variables.
319 Start by loading data. Start by loading data.
320 Maximum number of observations: Maximum number of observations:
321 setting to 0 includes all setting to 0 includes all
322 Select a dataset from your environment or sample dataset from a package. Select a dataset from your environment or sample dataset from a package.
323 Select a sample dataset from a package. Select a sample dataset from a package.
324 Data ready to be imported! Data ready to be imported!
325 Data has %s obs. of %s variables. Data has %s obs. of %s variables.
326 Data successfully imported! Data successfully imported!
327 Click to see data Click to see data
328 No data present. No data present.
329 You have provided a complete dataset with no missing values. You have provided a complete dataset with no missing values.

19
man/get_dimensions.Rd Normal file
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@ -0,0 +1,19 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/import_globalenv-ext.R
\name{get_dimensions}
\alias{get_dimensions}
\title{Extension of the helper function from datamods}
\usage{
get_dimensions(objs, filter_df = TRUE)
}
\arguments{
\item{objs}{objs}
\item{filter_df}{flag to only include data frames}
}
\value{
vector of data frames with the package names as attr
}
\description{
Extension of the helper function from datamods
}

8
man/import-file.Rd
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@ -12,7 +12,10 @@ import_file_ui(
preview_data = TRUE, preview_data = TRUE,
file_extensions = c(".csv", ".txt", ".xls", ".xlsx", ".rds", ".fst", ".sas7bdat", file_extensions = c(".csv", ".txt", ".xls", ".xlsx", ".rds", ".fst", ".sas7bdat",
".sav"), ".sav"),
layout_params = c("dropdown", "inline") layout_params = c("dropdown", "inline"),
limit_default = 10000,
limit_upper = 10000,
limit_lower = 0
) )
import_file_server( import_file_server(
@ -21,8 +24,7 @@ import_file_server(
show_data_in = c("popup", "modal"), show_data_in = c("popup", "modal"),
trigger_return = c("button", "change"), trigger_return = c("button", "change"),
return_class = c("data.frame", "data.table", "tbl_df", "raw"), return_class = c("data.frame", "data.table", "tbl_df", "raw"),
reset = reactive(NULL), reset = reactive(NULL)
limit = 1e+05
) )
} }
\arguments{ \arguments{

5
man/import-globalenv.Rd
View file

@ -19,7 +19,8 @@ import_globalenv_server(
show_data_in = c("popup", "modal"), show_data_in = c("popup", "modal"),
trigger_return = c("button", "change"), trigger_return = c("button", "change"),
return_class = c("data.frame", "data.table", "tbl_df", "raw"), return_class = c("data.frame", "data.table", "tbl_df", "raw"),
reset = reactive(NULL) reset = reactive(NULL),
limit_data = NULL
) )
} }
\arguments{ \arguments{
@ -43,6 +44,8 @@ use \code{NULL} for no title or a \code{shiny.tag} for a custom one.}
\item{return_class}{Class of returned data: \code{data.frame}, \code{data.table}, \code{tbl_df} (tibble) or \code{raw}.} \item{return_class}{Class of returned data: \code{data.frame}, \code{data.table}, \code{tbl_df} (tibble) or \code{raw}.}
\item{reset}{A \code{reactive} function that when triggered resets the data.} \item{reset}{A \code{reactive} function that when triggered resets the data.}
\item{limit_data}{upper limit to imported data}
} }
\description{ \description{
Let the user select a dataset from its own environment or from a package's environment. Let the user select a dataset from its own environment or from a package's environment.

17
man/launch_FreesearchR.Rd
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@ -4,10 +4,25 @@
\alias{launch_FreesearchR} \alias{launch_FreesearchR}
\title{Easily launch the FreesearchR app} \title{Easily launch the FreesearchR app}
\usage{ \usage{
launch_FreesearchR(...) launch_FreesearchR(
inlcude_globalenv = TRUE,
data_limit_default = 1000,
data_limit_upper = 1e+05,
data_limit_lower = 1,
...
)
} }
\arguments{ \arguments{
\item{data_limit_default}{default data set observations limit}
\item{data_limit_upper}{data set observations upper limit}
\item{data_limit_lower}{data set observations lower limit}
\item{...}{passed on to \code{shiny::runApp()}} \item{...}{passed on to \code{shiny::runApp()}}
\item{include_globalenv}{flag to include global env (local data) as option
when loading data}
} }
\value{ \value{
shiny app shiny app

3
man/limit_data_size.Rd
View file

@ -18,9 +18,10 @@ data.frame
This function may act to guard a hosted app against very large data sets in This function may act to guard a hosted app against very large data sets in
addition to the file size limitations. addition to the file size limitations.
The function will limit the data set by dropping rows. The function will limit the data set by dropping rows.
If limit is set to 0 or NULL, the original data set is returned.
} }
\examples{ \examples{
prod(dim(mtcars)) prod(dim(mtcars))
limit_data_size(mtcars) limit_data_size(mtcars,2)
limit_data_size(mtcars,100) limit_data_size(mtcars,100)
} }

540
renv.lock
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File diff suppressed because one or more lines are too long

101
renv/activate.R
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@ -2,7 +2,8 @@
local({ local({
# the requested version of renv # the requested version of renv
version <- "1.1.5" version <- "1.1.7"
attr(version, "md5") <- "dd5d60f155dadff4c88c2fc6680504b4"
attr(version, "sha") <- NULL attr(version, "sha") <- NULL
# the project directory # the project directory
@ -168,6 +169,16 @@ local({
if (quiet) if (quiet)
return(invisible()) return(invisible())
# also check for config environment variables that should suppress messages
# https://github.com/rstudio/renv/issues/2214
enabled <- Sys.getenv("RENV_CONFIG_STARTUP_QUIET", unset = NA)
if (!is.na(enabled) && tolower(enabled) %in% c("true", "1"))
return(invisible())
enabled <- Sys.getenv("RENV_CONFIG_SYNCHRONIZED_CHECK", unset = NA)
if (!is.na(enabled) && tolower(enabled) %in% c("false", "0"))
return(invisible())
msg <- sprintf(fmt, ...) msg <- sprintf(fmt, ...)
cat(msg, file = stdout(), sep = if (appendLF) "\n" else "") cat(msg, file = stdout(), sep = if (appendLF) "\n" else "")
@ -215,6 +226,16 @@ local({
section <- header(sprintf("Bootstrapping renv %s", friendly)) section <- header(sprintf("Bootstrapping renv %s", friendly))
catf(section) catf(section)
# try to install renv from cache
md5 <- attr(version, "md5", exact = TRUE)
if (length(md5)) {
pkgpath <- renv_bootstrap_find(version)
if (length(pkgpath) && file.exists(pkgpath)) {
file.copy(pkgpath, library, recursive = TRUE)
return(invisible())
}
}
# attempt to download renv # attempt to download renv
catf("- Downloading renv ... ", appendLF = FALSE) catf("- Downloading renv ... ", appendLF = FALSE)
withCallingHandlers( withCallingHandlers(
@ -240,7 +261,6 @@ local({
# add empty line to break up bootstrapping from normal output # add empty line to break up bootstrapping from normal output
catf("") catf("")
return(invisible()) return(invisible())
} }
@ -257,12 +277,20 @@ local({
repos <- Sys.getenv("RENV_CONFIG_REPOS_OVERRIDE", unset = NA) repos <- Sys.getenv("RENV_CONFIG_REPOS_OVERRIDE", unset = NA)
if (!is.na(repos)) { if (!is.na(repos)) {
# check for RSPM; if set, use a fallback repository for renv # split on ';' if present
rspm <- Sys.getenv("RSPM", unset = NA) parts <- strsplit(repos, ";", fixed = TRUE)[[1L]]
if (identical(rspm, repos))
repos <- c(RSPM = rspm, CRAN = cran)
return(repos) # split into named repositories if present
idx <- regexpr("=", parts, fixed = TRUE)
keys <- substring(parts, 1L, idx - 1L)
vals <- substring(parts, idx + 1L)
names(vals) <- keys
# if we have a single unnamed repository, call it CRAN
if (length(vals) == 1L && identical(keys, ""))
names(vals) <- "CRAN"
return(vals)
} }
@ -511,6 +539,51 @@ local({
} }
renv_bootstrap_find <- function(version) {
path <- renv_bootstrap_find_cache(version)
if (length(path) && file.exists(path)) {
catf("- Using renv %s from global package cache", version)
return(path)
}
}
renv_bootstrap_find_cache <- function(version) {
md5 <- attr(version, "md5", exact = TRUE)
if (is.null(md5))
return()
# infer path to renv cache
cache <- Sys.getenv("RENV_PATHS_CACHE", unset = "")
if (!nzchar(cache)) {
root <- Sys.getenv("RENV_PATHS_ROOT", unset = NA)
if (!is.na(root))
cache <- file.path(root, "cache")
}
if (!nzchar(cache)) {
tools <- asNamespace("tools")
if (is.function(tools$R_user_dir)) {
root <- tools$R_user_dir("renv", "cache")
cache <- file.path(root, "cache")
}
}
# start completing path to cache
file.path(
cache,
renv_bootstrap_cache_version(),
renv_bootstrap_platform_prefix(),
"renv",
version,
md5,
"renv"
)
}
renv_bootstrap_download_tarball <- function(version) { renv_bootstrap_download_tarball <- function(version) {
# if the user has provided the path to a tarball via # if the user has provided the path to a tarball via
@ -979,7 +1052,7 @@ local({
renv_bootstrap_validate_version_release <- function(version, description) { renv_bootstrap_validate_version_release <- function(version, description) {
expected <- description[["Version"]] expected <- description[["Version"]]
is.character(expected) && identical(expected, version) is.character(expected) && identical(c(expected), c(version))
} }
renv_bootstrap_hash_text <- function(text) { renv_bootstrap_hash_text <- function(text) {
@ -1181,6 +1254,18 @@ local({
} }
renv_bootstrap_cache_version <- function() {
# NOTE: users should normally not override the cache version;
# this is provided just to make testing easier
Sys.getenv("RENV_CACHE_VERSION", unset = "v5")
}
renv_bootstrap_cache_version_previous <- function() {
version <- renv_bootstrap_cache_version()
number <- as.integer(substring(version, 2L))
paste("v", number - 1L, sep = "")
}
renv_json_read <- function(file = NULL, text = NULL) { renv_json_read <- function(file = NULL, text = NULL) {
jlerr <- NULL jlerr <- NULL

1
renv/settings.json
View file

@ -10,6 +10,7 @@
"ppm.enabled": null, "ppm.enabled": null,
"ppm.ignored.urls": [], "ppm.ignored.urls": [],
"r.version": null, "r.version": null,
"snapshot.dev": false,
"snapshot.type": "explicit", "snapshot.type": "explicit",
"use.cache": true, "use.cache": true,
"vcs.ignore.cellar": true, "vcs.ignore.cellar": true,