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refined missingness evaluation

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Andreas Gammelgaard Damsbo 2025-12-11 17:22:47 +01:00
commit 35afbc1dc9
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21 changed files with 1358 additions and 760 deletions
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R/missings-module.R
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@ -75,15 +75,15 @@ data_missings_server <- function(id,
shiny::req(data())
vectorSelectInput(
inputId = ns("missings_method"),
label = i18n$t("Select missings analysis to apply"),
label = i18n$t("Analysis method for missingness overview"),
choices = setNames(
c(
"predictors",
"outcome"
),
c(
i18n$t("Variables"),
i18n$t("By outcome")
i18n$t("Overview of missings across variables"),
i18n$t("Overview of difference in variables by missing status in outcome")
)
)
)
@ -96,15 +96,19 @@ data_missings_server <- function(id,
shiny::req(input$missings_method)
# browser()
if (input$missings_method == "predictors") {
label <- i18n$t("Select a variable for grouped overview")
df <- data_type_filter(data(), type = c("categorical", "dichotomous"))
col_subset <- c("none", names(df))
} else {
label <- i18n$t("Select outcome variable for overview")
df <- datar()[apply(datar(), 2, anyNA)]
col_subset <- names(df)
}
columnSelectInput(
inputId = ns("missings_var"),
label = i18n$t("Select variable to stratify analysis"),
label = label,
data = df,
col_subset = c("none", names(df)),
col_subset = col_subset,
none_label = i18n$t("No variable")
)
})
@ -144,7 +148,11 @@ data_missings_server <- function(id,
# if (is.null(variabler()) || variabler() == "" || !variabler() %in% names(data()) || variabler() == "none") {
# tbl <- rv$data()
if (anyNA(datar())) {
title <- i18n$t("No variable chosen for analysis")
if (input$missings_method == "predictors") {
title <- i18n$t("Overview of missing observations")
} else {
title <- i18n$t("No outcome measure chosen")
}
} else {
title <- i18n$t("No missing observations")
}