mirror of
https://github.com/agdamsbo/REDCapCAST.git
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128 lines
3.8 KiB
R
128 lines
3.8 KiB
R
utils::globalVariables(c("redcap_wider",
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"event.glue",
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"inst.glue"))
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#' @title Redcap Wider
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#' @description Converts a list of REDCap data frames from long to wide format.
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#' Handles longitudinal projects, but not yet repeated instruments.
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#' @param data A list of data frames.
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#' @param event.glue A dplyr::glue string for repeated events naming
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#' @param inst.glue A dplyr::glue string for repeated instruments naming
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#' @return The list of data frames in wide format.
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#' @export
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#' @importFrom tidyr pivot_wider
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#' @importFrom tidyselect all_of
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#' @importFrom purrr reduce
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#'
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#' @examples
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#' # Longitudinal
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#' list1 <- list(data.frame(record_id = c(1,2,1,2),
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#' redcap_event_name = c("baseline", "baseline", "followup", "followup"),
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#' age = c(25,26,27,28)),
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#' data.frame(record_id = c(1,2),
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#' redcap_event_name = c("baseline", "baseline"),
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#' gender = c("male", "female")))
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#' redcap_wider(list1)
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#' # Simpel with two instruments
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#' list2 <- list(data.frame(record_id = c(1,2),
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#' age = c(25,26)),
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#' data.frame(record_id = c(1,2),
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#' gender = c("male", "female")))
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#' redcap_wider(list2)
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#' # Simple with single instrument
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#' list3 <- list(data.frame(record_id = c(1,2),
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#' age = c(25,26)))
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#' redcap_wider(list3)
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#' # Longitudinal with repeatable instruments
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#' list4 <- list(data.frame(record_id = c(1,2,1,2),
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#' redcap_event_name = c("baseline", "baseline", "followup", "followup"),
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#' age = c(25,26,27,28)),
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#' data.frame(record_id = c(1,1,1,1,2,2,2,2),
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#' redcap_event_name = c("baseline", "baseline", "followup", "followup",
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#' "baseline", "baseline", "followup", "followup"),
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#' redcap_repeat_instrument = "walk",
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#' redcap_repeat_instance=c(1,2,1,2,1,2,1,2),
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#' dist = c(40, 32, 25, 33, 28, 24, 23, 36)),
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#' data.frame(record_id = c(1,2),
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#' redcap_event_name = c("baseline", "baseline"),
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#' gender = c("male", "female")))
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#'redcap_wider(list4)
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redcap_wider <-
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function(data,
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event.glue = "{.value}_{redcap_event_name}",
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inst.glue = "{.value}_{redcap_repeat_instance}") {
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if (!is.repeated_longitudinal(data)) {
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if (is.list(data)) {
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if (length(data) == 1) {
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out <- data[[1]]
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} else {
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out <- data |> purrr::reduce(dplyr::left_join)
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}
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} else if (is.data.frame(data)){
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out <- data
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}
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} else {
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id.name <- do.call(c, lapply(data, names))[[1]]
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l <- lapply(data, function(i) {
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rep_inst <- "redcap_repeat_instrument" %in% names(i)
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if (rep_inst) {
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k <- lapply(split(i, f = i[[id.name]]), function(j) {
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cname <- colnames(j)
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vals <-
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cname[!cname %in% c(
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id.name,
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"redcap_event_name",
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"redcap_repeat_instrument",
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"redcap_repeat_instance"
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)]
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s <- tidyr::pivot_wider(
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j,
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names_from = "redcap_repeat_instance",
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values_from = all_of(vals),
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names_glue = inst.glue
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)
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s[!colnames(s) %in% c("redcap_repeat_instrument")]
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})
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i <- Reduce(dplyr::bind_rows, k)
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}
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event <- "redcap_event_name" %in% names(i)
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if (event) {
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event.n <- length(unique(i[["redcap_event_name"]])) > 1
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i[["redcap_event_name"]] <-
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gsub(" ", "_", tolower(i[["redcap_event_name"]]))
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if (event.n) {
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cname <- colnames(i)
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vals <- cname[!cname %in% c(id.name, "redcap_event_name")]
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s <- tidyr::pivot_wider(
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i,
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names_from = "redcap_event_name",
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values_from = all_of(vals),
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names_glue = event.glue
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)
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s[colnames(s) != "redcap_event_name"]
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} else {
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i[colnames(i) != "redcap_event_name"]
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}
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} else {
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i
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}
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})
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out <- data.frame(Reduce(f = dplyr::full_join, x = l))
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}
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out
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}
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