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revised data types

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Andreas Gammelgaard Damsbo 2025-04-22 09:58:34 +02:00
commit aaceb55fe8
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5 changed files with 84 additions and 38 deletions
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21
R/regression_model.R
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@ -279,11 +279,11 @@ data_type <- function(data) {
if (identical("logical", cl_d) | length(unique(data)) == 2) {
out <- "dichotomous"
} else {
if (is.ordered(data)) {
out <- "ordinal"
} else {
# if (is.ordered(data)) {
# out <- "ordinal"
# } else {
out <- "categorical"
}
# }
}
} else if (identical(cl_d, "character")) {
out <- "text"
@ -310,7 +310,16 @@ data_type <- function(data) {
#' @examples
#' data_types()
data_types <- function() {
c("dichotomous", "ordinal", "categorical", "datatime", "continuous", "text", "empty", "monotone", "unknown")
list(
"empty" = list(descr="Variable of all NAs",classes="Any class"),
"monotone" = list(descr="Variable with only one unique value",classes="Any class"),
"dichotomous" = list(descr="Variable with only two unique values",classes="Any class"),
"categorical"= list(descr="Factor variable",classes="factor (ordered or unordered)"),
"text"= list(descr="Character variable",classes="character"),
"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")
)
}
@ -351,7 +360,7 @@ supported_functions <- function() {
polr = list(
descr = "Ordinal logistic regression model",
design = "cross-sectional",
out.type = c("ordinal", "categorical"),
out.type = c("categorical"),
fun = "MASS::polr",
args.list = list(
Hess = TRUE,