R/CH_SZWT_C_L25.R

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

##'CH_SZWT_C_L25
#' @param KRdata  data.frame from surveyPrev::getDHSdata
#'
#' @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
#'
#' @author Miaolei Bao, Yunhan Wu, Qianyu Dong
#' @examples
#' \dontrun{
#' dhsData <- getDHSdata(country = "Zambia", indicator = "CH_SZWT_C_L25", year = 2018)
#' }
#'
#' @export
CH_SZWT_C_L25 <- function(KRdata){
# /*****************************************************************************************************
# Program: 			  CH_SIZE.R
# Purpose: 		  	Code child size variables.
# Data inputs: 		KR dataset
# Data outputs:		coded variables
# Author:				  Shireen Assaf
# Date last modified: August 1 2022 by Shireen Assaf 
# *****************************************************************************************************/
# 
# /*----------------------------------------------------------------------------
# Variables created in this file:
# ch_size_birth	"Size of child at birth as reported by mother"
# ch_report_bw	"Has a reported birth weight"
# ch_below_2p5	"Birth weight less than 2.5 kg"
# ----------------------------------------------------------------------------*/

# weight variable 
KRdata <- KRdata %>%
  mutate(wt = v005/1000000)

# //Child's size at birth
KRdata <- KRdata %>%
  mutate(ch_size_birth =
           case_when(
             m18==5  ~ 1 ,
             m18==4  ~ 2 ,
             m18<=3  ~ 3 ,
             m18==8 | m18==9 ~ 9)) %>%
  set_value_labels(ch_size_birth = c("Very small" = 1, "Smaller than average"=2, "Average or larger"=3, "Don't know/missing"=9)) %>%
  set_variable_labels(ch_size_birth = "Size of child at birth as reported by mother")

# //Child's reported birth weight
KRdata <- KRdata %>%
  mutate(ch_report_bw = 
           case_when(
             m19<=9000 ~ 1 ,
             TRUE ~ 0 )) %>%
  set_value_labels(ch_report_bw = c("Yes" = 1, "No"=0)) %>%
  set_variable_labels(ch_report_bw = "Has a reported birth weight")
 
# //Child before 2.5kg
KRdata <- KRdata %>%
  mutate(ch_below_2p5 = 
           case_when(
             m19<2500 & ch_report_bw==1 ~ 1 ,
             ch_report_bw==1 ~ 0 )) %>%
  set_value_labels(ch_below_2p5 = c("Yes" = 1, "No"=0)) %>%
  set_variable_labels(ch_below_2p5 = "Birth weight less than 2.5 kg")

colnames(KRdata)[colnames(KRdata) == 'ch_below_2p5'] <- 'value'
return(KRdata)
}