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