mirror of
https://github.com/agdamsbo/REDCapCAST.git
synced 2024-11-27 15:21:55 +01:00
added option to export "both" raw and label by labelling raw data to preserve as much information as possible
This commit is contained in:
parent
57f9f23ece
commit
2ba46e8e7a
165
R/easy_redcap.R
165
R/easy_redcap.R
@ -31,6 +31,7 @@ easy_redcap <- function(project.name, widen.data = TRUE, uri, ...) {
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out <- read_redcap_tables(
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uri = uri,
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token = key,
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raw_or_label = "both",
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...
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)
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@ -40,167 +41,3 @@ easy_redcap <- function(project.name, widen.data = TRUE, uri, ...) {
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out
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}
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#' REDCap read function to preserve field labels and all factor levels
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#'
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#' @description
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#' This works very much as `read_redcap_tables()` and might end up there
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#'
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#'
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#' @param uri REDCap database API uri
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#' @param token API token
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#' @param records records to download
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#' @param fields fields to download
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#' @param events events to download
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#' @param forms forms to download
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#' @param split_forms Whether to split "repeating" or "all" forms, default is
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#' "all".
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#'
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#' @return data.frame or list
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#' @export
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#'
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read_redcap_labelled <- function(uri,
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token,
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records = NULL,
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fields = NULL,
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events = NULL,
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forms = NULL,
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split_forms = "all") {
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m <-
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REDCapR::redcap_metadata_read(redcap_uri = uri, token = token)[["data"]]
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# Tests
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if (!is.null(fields)) {
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fields_test <- fields %in% c(m$field_name, paste0(unique(m$form_name), "_complete"))
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if (any(!fields_test)) {
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print(paste0(
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"The following field names are invalid: ",
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paste(fields[!fields_test], collapse = ", "), "."
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))
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stop("Not all supplied field names are valid")
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}
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}
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if (!is.null(forms)) {
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forms_test <- forms %in% unique(m$form_name)
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if (any(!forms_test)) {
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print(paste0(
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"The following form names are invalid: ",
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paste(forms[!forms_test], collapse = ", "), "."
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))
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stop("Not all supplied form names are valid")
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}
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}
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if (!is.null(events)) {
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arm_event_inst <- REDCapR::redcap_event_instruments(
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redcap_uri = uri,
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token = token
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)
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event_test <- events %in% unique(arm_event_inst$data$unique_event_name)
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if (any(!event_test)) {
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print(paste0(
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"The following event names are invalid: ",
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paste(events[!event_test], collapse = ", "), "."
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))
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stop("Not all supplied event names are valid")
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}
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}
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# Getting dataset
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d <- REDCapR::redcap_read(
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redcap_uri = uri,
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token = token,
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fields = fields,
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events = events,
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forms = forms,
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records = records,
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raw_or_label = "raw"
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)[["data"]]
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# Applying labels
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d <- purrr::imap(d, \(.x, .i){
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if (.i %in% m$field_name) {
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# Does not handle checkboxes
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out <- set_attr(.x,
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label = clean_field_label(m$field_label[m$field_name == .i]),
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attr = "label"
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)
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out
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} else {
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.x
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}
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}) |> dplyr::bind_cols()
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d <- purrr::imap(d, \(.x, .i){
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if (any(c("radio", "dropdown") %in% m$field_type[m$field_name == .i])) {
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format_redcap_factor(.x, m$select_choices_or_calculations[m$field_name == .i])
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} else {
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.x
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}
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}) |> dplyr::bind_cols()
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# Process repeat instrument naming
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# Removes any extra characters other than a-z, 0-9 and "_", to mimic raw
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# instrument names.
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if ("redcap_repeat_instrument" %in% names(d)) {
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d$redcap_repeat_instrument <- clean_redcap_name(d$redcap_repeat_instrument)
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}
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# Processing metadata to reflect focused dataset
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m <- focused_metadata(m, names(d))
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# Splitting
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out <- REDCap_split(d,
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m,
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forms = split_forms,
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primary_table_name = ""
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)
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sanitize_split(out)
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}
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#' Very simple function to remove rich text formatting from field label
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#' and save the first paragraph ('<p>...</p>').
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#'
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#' @param data field label
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#'
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#' @return character vector
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#' @export
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#'
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#' @examples
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#' clean_field_label("<div class=\"rich-text-field-label\"><p>Fazekas score</p></div>")
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clean_field_label <- function(data) {
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out <- data |>
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lapply(\(.x){
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unlist(strsplit(.x, "</"))[1]
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}) |>
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lapply(\(.x){
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splt <- unlist(strsplit(.x, ">"))
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splt[length(splt)]
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})
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Reduce(c, out)
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}
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format_redcap_factor <- function(data, meta) {
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lvls <- strsplit(meta, " | ", fixed = TRUE) |>
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unlist() |>
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lapply(\(.x){
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splt <- unlist(strsplit(.x, ", "))
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stats::setNames(splt[1], nm = paste(splt[-1], collapse = ", "))
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}) |>
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(\(.x){
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Reduce(c, .x)
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})()
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set_attr(data, label = lvls, attr = "labels") |>
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set_attr(data, label = "labelled", attr = "class") |>
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as_factor()
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}
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@ -11,7 +11,15 @@
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#' @param fields fields to download
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#' @param events events to download
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#' @param forms forms to download
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#' @param raw_or_label raw or label tags
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#' @param raw_or_label raw or label tags. Can be
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#'
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#' * "raw": Standard [REDCapR] method to get raw values.
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#' * "label": Standard [REDCapR] method to get label values.
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#' * "both": Get raw values with REDCap labels applied as labels. Use
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#' [as_factor()] to format factors with original labels and use the
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#' [gtsummary] package to easily get beautiful tables with original labels
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#' from REDCap. Use [fct_drop()] to drop empty levels.
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#'
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#' @param split_forms Whether to split "repeating" or "all" forms, default is
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#' all.
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#'
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@ -70,6 +78,12 @@ read_redcap_tables <- function(uri,
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}
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}
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if (raw_or_label=="both"){
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rorl <- "raw"
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} else {
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rorl <- raw_or_label
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}
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# Getting dataset
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d <- REDCapR::redcap_read(
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redcap_uri = uri,
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@ -78,9 +92,16 @@ read_redcap_tables <- function(uri,
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events = events,
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forms = forms,
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records = records,
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raw_or_label = raw_or_label
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raw_or_label = rorl
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)[["data"]]
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if (raw_or_label=="both"){
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d <- apply_field_label(data=d,meta=m)
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d <- apply_factor_labels(data=d,meta=m)
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}
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# Process repeat instrument naming
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# Removes any extra characters other than a-z, 0-9 and "_", to mimic raw
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# instrument names.
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@ -101,3 +122,84 @@ read_redcap_tables <- function(uri,
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sanitize_split(out)
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}
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#' Very simple function to remove rich text formatting from field label
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#' and save the first paragraph ('<p>...</p>').
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#'
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#' @param data field label
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#'
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#' @return character vector
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#' @export
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#'
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#' @examples
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#' clean_field_label("<div class=\"rich-text-field-label\"><p>Fazekas score</p></div>")
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clean_field_label <- function(data) {
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out <- data |>
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lapply(\(.x){
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unlist(strsplit(.x, "</"))[1]
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}) |>
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lapply(\(.x){
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splt <- unlist(strsplit(.x, ">"))
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splt[length(splt)]
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})
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Reduce(c, out)
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}
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format_redcap_factor <- function(data, meta) {
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lvls <- strsplit(meta, " | ", fixed = TRUE) |>
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unlist() |>
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lapply(\(.x){
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splt <- unlist(strsplit(.x, ", "))
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stats::setNames(splt[1], nm = paste(splt[-1], collapse = ", "))
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}) |>
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(\(.x){
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Reduce(c, .x)
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})()
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set_attr(data, label = lvls, attr = "labels") |>
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set_attr(data, label = "redcapcast_labelled", attr = "class")
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}
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#' Apply REDCap filed labels to data frame
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#'
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#' @param data REDCap exported data set
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#' @param meta REDCap data dictionary
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#'
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#' @return data.frame
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#' @export
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#'
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apply_field_label <- function(data,meta){
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purrr::imap(data, \(.x, .i){
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if (.i %in% meta$field_name) {
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# Does not handle checkboxes
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out <- set_attr(.x,
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label = clean_field_label(meta$field_label[meta$field_name == .i]),
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attr = "label"
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)
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out
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} else {
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.x
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}
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}) |> dplyr::bind_cols()
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}
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#' Preserve all factor levels from REDCap data dictionary in data export
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#'
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#' @param data REDCap exported data set
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#' @param meta REDCap data dictionary
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#'
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#' @return data.frame
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#' @export
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#'
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apply_factor_labels <- function(data,meta){
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purrr::imap(data, \(.x, .i){
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if (any(c("radio", "dropdown") %in% meta$field_type[meta$field_name == .i])) {
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format_redcap_factor(.x, meta$select_choices_or_calculations[meta$field_name == .i])
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} else {
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.x
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}
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}) |> dplyr::bind_cols()
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}
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@ -8,6 +8,8 @@
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\alias{as_factor.character}
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\alias{as_factor.haven_labelled}
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\alias{as_factor.labelled}
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\alias{as_factor.redcapcast_labelled}
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\alias{as_factor.data.frame}
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\title{Convert labelled vectors to factors while preserving attributes}
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\usage{
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as_factor(x, ...)
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@ -33,6 +35,15 @@ as_factor(x, ...)
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ordered = FALSE,
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...
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)
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\method{as_factor}{redcapcast_labelled}(
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x,
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levels = c("default", "labels", "values", "both"),
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ordered = FALSE,
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...
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)
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\method{as_factor}{data.frame}(x, ..., only_labelled = TRUE)
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}
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\arguments{
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\item{x}{Object to coerce to a factor.}
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@ -49,6 +60,8 @@ as_factor(x, ...)
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\item{ordered}{If `TRUE` create an ordered (ordinal) factor, if
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`FALSE` (the default) create a regular (nominal) factor.}
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\item{only_labelled}{Only apply to labelled columns?}
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}
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\description{
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This extends [forcats::as_factor()] as well as [haven::as_factor()], by appending
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@ -1,5 +1,5 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/easy_redcap.R
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% Please edit documentation in R/read_redcap_tables.R
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\name{clean_field_label}
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\alias{clean_field_label}
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\title{Very simple function to remove rich text formatting from field label
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@ -11,7 +11,7 @@ ds2dd(
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field.type = "text",
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field.label = NULL,
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include.column.names = FALSE,
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metadata = REDCapCAST::redcap_meta_default()
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metadata = names(REDCapCAST::redcapcast_meta)
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)
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}
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\arguments{
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@ -34,7 +34,7 @@ names.}
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column names for original data set for upload.}
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\item{metadata}{Metadata column names. Default is the included
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REDCapCAST::redcap_meta_default.}
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names(REDCapCAST::redcapcast_meta).}
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}
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\value{
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data.frame or list of data.frame and vector
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18
man/fct_drop.Rd
Normal file
18
man/fct_drop.Rd
Normal file
@ -0,0 +1,18 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/fct_drop.R
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\name{fct_drop}
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\alias{fct_drop}
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\alias{fct_drop.data.frame}
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\title{Drop unused levels preserving label data}
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\usage{
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fct_drop.data.frame(x, ...)
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}
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\arguments{
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\item{x}{Factor to drop unused levels}
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\item{...}{Other arguments passed down to method.}
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}
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\description{
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This extends [forcats::fct_drop()] to natively work across a data.frame and
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replace [base::droplevels()].
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}
|
28
man/is.labelled.Rd
Normal file
28
man/is.labelled.Rd
Normal file
@ -0,0 +1,28 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/as_factor.R
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\name{is.labelled}
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\alias{is.labelled}
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\title{Tests for multiple label classes}
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\usage{
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is.labelled(
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x,
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classes = c("redcapcast_labelled", "haven_labelled", "labelled")
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)
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}
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\arguments{
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\item{x}{data}
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\item{classes}{classes to test}
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}
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\value{
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logical
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}
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\description{
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Tests for multiple label classes
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}
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\examples{
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structure(c(1, 2, 3, 2, 10, 9),
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labels = c(Unknown = 9, Refused = 10),
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class = "haven_labelled"
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) |> is.labelled()
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}
|
@ -1,38 +0,0 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/easy_redcap.R
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\name{read_redcap_labelled}
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\alias{read_redcap_labelled}
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\title{REDCap read function to preserve field labels and all factor levels}
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\usage{
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read_redcap_labelled(
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uri,
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token,
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records = NULL,
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fields = NULL,
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events = NULL,
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forms = NULL,
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split_forms = "all"
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)
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}
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\arguments{
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\item{uri}{REDCap database API uri}
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\item{token}{API token}
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\item{records}{records to download}
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\item{fields}{fields to download}
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\item{events}{events to download}
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\item{forms}{forms to download}
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\item{split_forms}{Whether to split "repeating" or "all" forms, default is
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"all".}
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}
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\value{
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data.frame or list
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}
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\description{
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This works very much as `read_redcap_tables()` and might end up there
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}
|
@ -28,7 +28,14 @@ read_redcap_tables(
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\item{forms}{forms to download}
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|
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\item{raw_or_label}{raw or label tags}
|
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\item{raw_or_label}{raw or label tags. Can be
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|
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* "raw": Standard [REDCapR] method to get raw values.
|
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* "label": Standard [REDCapR] method to get label values.
|
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* "both": Get raw values with REDCap labels applied as labels. Use
|
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[as_factor()] to format factors with original labels and use the
|
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[gtsummary] package to easily get beautiful tables with original labels
|
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from REDCap. Use [fct_drop()] to drop empty levels.}
|
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|
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\item{split_forms}{Whether to split "repeating" or "all" forms, default is
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all.}
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|
@ -1,20 +0,0 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/ds2dd_detailed.R
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\name{redcap_meta_default}
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\alias{redcap_meta_default}
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\title{Default column names of a REDCap data dictionary}
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\usage{
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redcap_meta_default(...)
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}
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\arguments{
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\item{...}{ignored for now}
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}
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\value{
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character vector
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}
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\description{
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Default column names of a REDCap data dictionary
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}
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\examples{
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dput(redcap_meta_default())
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}
|
@ -36,14 +36,14 @@ str(ds)
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|
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```{r}
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ds|>
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ds2dd_detailed()|>
|
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ds2dd_detailed(metadata = names(REDCapCAST::redcapcast_meta))|>
|
||||
purrr::pluck("data") |>
|
||||
str()
|
||||
```
|
||||
|
||||
```{r}
|
||||
ds|>
|
||||
ds2dd_detailed()|>
|
||||
ds2dd_detailed(metadata = names(REDCapCAST::redcapcast_meta))|>
|
||||
purrr::pluck("meta") |>
|
||||
head(10)
|
||||
```
|
||||
|
Loading…
Reference in New Issue
Block a user