REDCapCAST/REDCap_split.r

115 lines
2.8 KiB
R

#' Split REDCap repeating instruments table into multiple tables
#'
#' This will take a raw \code{data.frame} from REDCap and split it into a base table
#' and give individual tables for each repeating instrument. Metadata
#' is used to determine which fields should be included in each resultant table.
#'
#' @param records \code{data.frame} containing project records
#' @param metadata \code{data.frame} containing project metadata (the data dictionary)
#' @author Paul W. Egeler, M.S., GStat
#' @examples
#' \dontrun{
#' library(jsonlite)
#' library(RCurl)
#'
#' # Get the metadata
#' result.meta <- postForm(
#' api_url,
#' token = api_token,
#' content = 'metadata',
#' format = 'json'
#' )
#'
#' # Get the records
#' result.record <- postForm(
#' uri = api_url,
#' token = api_token,
#' content = 'record',
#' format = 'json',
#' returnFormat = 'json'
#' )
#'
#' # Convert JSON to data.frames
#' records <- fromJSON(result.record)
#' metadata <- fromJSON(result.meta)
#'
#' # Split the data.frame into a list of data.frames
#' REDCap_split(records, metadata)
#' }
#' @return a list of data.frames
#' @export
REDCap_split <- function(records, metadata) {
stopifnot(all(sapply(list(records,metadata), inherits, "data.frame")))
# Check to see if there were any repeating instruments
if (!any(names(records) == "redcap_repeat_instrument")) {
message("There are no repeating instruments in this data.")
return(list(records))
}
# Find the fields and associated form
fields <- metadata[
!metadata$field_type %in% c("descriptive", "checkbox"),
c("field_name", "form_name")
]
if (any(metadata$field_type == "checkbox")) {
checkbox_basenames <- metadata[
metadata$field_type == "checkbox",
c("field_name", "form_name")
]
checkbox_fields <-
do.call(
"rbind",
apply(
checkbox_basenames,
1,
function(x)
data.frame(
field_name = names(records)[grepl(paste0("^", x[1], "___.+$"), names(records))],
form_name = x[2],
stringsAsFactors = FALSE,
row.names = NULL
)
)
)
fields <- rbind(fields, checkbox_fields)
}
# Identify the subtables in the data
subtables <- unique(records$redcap_repeat_instrument)
subtables <- subtables[subtables != ""]
# Split the table based on instrument
out <- split.data.frame(records, records$redcap_repeat_instrument)
# Delete the variables that are not relevant
for (i in names(out)) {
if (i == "") {
out[[which(names(out) == "")]] <-
out[[which(names(out) == "")]][fields[!fields[,2] %in% subtables, 1]]
} else {
out[[i]] <-
out[[i]][c(names(records[1:3]),fields[fields[,2] == i, 1])]
}
}
return(out)
}