REDCapCAST/R/read_redcap_tables.R

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2023-02-28 09:54:03 +01:00
#' Download REDCap data
#'
#' Wrapper function for using REDCapR::redcap_read and REDCapRITS::REDCap_split
#' including some clean-up. Works with longitudinal projects with repeating
#' instruments.
#' @param uri REDCap database uri
#' @param token API token
#' @param records records to download
#' @param fields fields to download
#' @param events events to download
#' @param forms forms to download
#' @param raw_or_label raw or label tags
#' @param generics vector of auto-generated generic variable names to
#' ignore when discarding empty rows
#' @param ... ekstra parameters for REDCapR::redcap_read_oneshot
#'
#' @return list of instruments
#' @importFrom REDCapR redcap_metadata_read redcap_read
#' @export
#'
#' @examples
#' # Examples will be provided later
read_redcap_tables <- function(uri,
token,
records = NULL,
fields = NULL,
events = NULL,
forms = NULL,
raw_or_label = "label",
generics = c(
"record_id",
"redcap_event_name",
"redcap_repeat_instrument",
"redcap_repeat_instance"
),
...) {
# Notes to self: Based on the metadata, this functionality could be
# introduced without using the REDCapRITS package.. To be tried..
#
# This does not handle repeated instruments!! This should be implemented.
d <- REDCapR::redcap_read_oneshot(
redcap_uri = uri,
token = token,
fields = fields,
events = events,
forms = forms,
records = records,
raw_or_label = raw_or_label,
...
)
m <-
REDCapR::redcap_metadata_read (redcap_uri = uri, token = token)
l <- REDCap_split(d$data,
m$data[m$data$field_name %in% names(d$data), ],
forms = "all")
lapply(l, function(i) {
if (ncol(i) > 2) {
s <- data.frame(i[, !colnames(i) %in% generics])
i[!apply(is.na(s), MARGIN = 1, FUN = all), ]
} else {
i
}
})
}