R/CM_ECMR_C_U5M.R

In surveyPrev: Mapping the Prevalence of Binary Indicators using Survey Data in Small Areas

##' CM_ECMR_C_U5M u5mr 10 years prior to survey.
##'
##' BR
#' @param Rdata  data.frame from surveyPrev::getDHSdata
#' @param mort.cut  age group cutoffs for hazard calculation. Constant hazards are assumed to be within the specified cutoffs.
#' @param mort.year The number of years preceding survey. Set to be 10.
#'
#' @return A partially processed data.frame that will be used in surveyPrev::getDHSindicator. The whole function can be used as a parameter in surveyPrev::getDHSindicator
#'
#' @examples
#' \dontrun{
#' dhsData <- getDHSdata(country = "Zambia", indicator = "CM_ECMR_C_U5M", year = 2018)
#' }
#'
#' @export
#'
CM_ECMR_C_U5M<- function(Rdata, mort.cut = c(1, 2, 6, 12, 24, 36, 48, 60), mort.year = 10){

    Rdata$b5 <- labelled::to_factor(Rdata$b5)
    Rdata <- subset(Rdata, v008-12*(mort.year + 5)-b3 < 0)
    Rdata$strata <- NA
    # Get birth coded as person-months
    # year.cut is specified for a wide range to avoid SUMMER's rule of dropping partial year observations for now
    raw.dat.tmp <- SUMMER::getBirths(data = Rdata,  strata = c("strata"),
                   year.cut = c(1900, 2100), month.cut = mort.cut)
    # now we need to remove person months not in the [-X, 0] range (between -X-5 and -X)
    # id.new is the row number in the original input
    Rdata$id.new <- 1:dim(Rdata)[1]
    raw.dat.tmp1 <- left_join(raw.dat.tmp, Rdata[, c("id.new", "v008")])
    raw.dat.tmp1 <- subset(raw.dat.tmp1, v008 - mort.year*12 < obsStart)
    raw.dat.tmp <- raw.dat.tmp1[, -which(colnames(raw.dat.tmp1) == "v008")]
    raw.dat.tmp$value <- raw.dat.tmp$died


  return(raw.dat.tmp)
}