#' Make start-end data:
#'
#' * We still want one line per patient, and thus move some of the variables from the final registration to the patients start registration.
#' * The End registrations will appear twice in this data. Once as in the normal data and in addition added to the start registrations as new variables
#'
#' Note: This function's name when writing aarsrapport 2019 (in 2020) was: make26_dataStartEnd()
#'
#' @param myInData RegData
#'
#' @return RegDataStartEnd
#' @export
#'
#' @examples
fun2_4_1_RegDataStartEnd <- function(myInData){
#Transform to tibble
RegData <- as_tibble(myInData)
# Make the primary data set:
## Make one dataset with only the end registrations
RegDataEnd <- RegData[which(RegData$RegRegtype %in% c(5,6,98,99)), ]
#note: some observations have RegRegType == 0, which is because these registrations are not yet fully made
## Join the full data with the end registratons, to get one dataset with on line per patient, with all scores from start and end registrations
## Make new columm called id, in each dataset to merge/join by:
RegData$id <- RegData$ForlopsID
RegDataEnd$id <- as.numeric(RegDataEnd$RegTilhorendeStartReg)
##Join:
RegDataStartEnd <- dplyr::full_join(RegData, RegDataEnd, by = "id")#OBS -all combinations of multiple matches are returned: For every end registration that is connected to one and the same start registration (which should not happen, but still does happen because people register/choose wrong start registration to connect the end registrations to) - additional start-registrations are made, because of how we choose to do this merge.
#we remove multiple matches. Of the multiple matches, we keep the matches with the oldest end date (HovedDato_FRMT.y) (by use of arrange first):
RegDataStartEnd <- RegDataStartEnd %>%
arrange(ForlopsID.x, HovedDato_FRMT.y) %>%# Together with distinct below: to sort and keep olderst end registration
distinct(ForlopsID.x, .keep_all = TRUE)
RegDataStartEnd
}
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