REDCapCAST/R/redcap_wider.R

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