R/immigration.R

In cchsflow: Transforming and Harmonizing CCHS Variables

#' @title Immigration by ethnicity and settlement
#' 
#' @description This function creates a categorical variable based on 
#' immigrant status (SDCFIMM), country of birth (SDCGCBG), ethnicity (SDCGCGT), 
#' and time in Canada (SDCGRES). 
#' 
#' @details 
#' immigration_der uses the CCHS variables that have been transformed by 
#' cchsflow. In order to generate a value for BMI across CCHS cycles, 
#' the following SDC variables must be transformed and harmonized.
#' 
#' 
#' @param SDCFIMM Immigrant status (1-immigrant, 2-non-immigrant)
#' 
#' @param SDCGCBG Country of birth (1-Canada, 2-Outside of Canada)
#' 
#' @param SDCGCGT Cultural or racial origin (1-white, 2-visible minority)
#' 
#' @param SDCGRES Length/time in Canada since immigration (1- 0-9 years, 2- 10+ 
#' years)
#' 
#' @return Categorical variable (immigration_der) with six categories:
#' 
#'  \itemize{
#'   \item 1 - White Canada-born
#'   \item 2 - Non-white Canadian born
#'   \item 3 - White immigrant born outside of Canada (0-9 years in Canada)
#'   \item 4 - Non-white immigrant born outside of Canada (0-9 years in Canada)
#'   \item 5 - White immigrant born outside of Canada (10+ years in Canada)
#'   \item 6 - Non-white immigrant born outside of Canada (10+ years in Canada)
#' }
#' 
#' @examples
#' # Using immigration_fun() to create immigration_der values across CCHS cycles
#' # immigration_fun() is specified in variable_details.csv along with the
#' # CCHS variables and cycles included.
#' 
#' # To transform immigration_der, use rec_with_table() for each CCHS cycle
#' # and specify immigration_der, along with the various SDC variables.
#' # Then by using merge_rec_data() you can combine immigration_der across cycles.
#' 
#' library(cchsflow)
#' immigration2001 <- rec_with_table(
#'   cchs2001_p, c(
#'     "SDCFIMM", "SDCGCBG", "SDCGCGT", "SDCGRES", "immigration_der"
#'   )
#' )
#' 
#' head(immigration2001)
#' 
#' immigration2009_2010 <- rec_with_table(
#'   cchs2009_2010_p, c(
#'     "SDCFIMM", "SDCGCBG", "SDCGCGT", "SDCGRES", "immigration_der"
#'   )
#' )
#' 
#' tail(immigration2009_2010)
#' 
#' combined_immigration <- merge_rec_data(immigration2001, immigration2009_2010)
#' 
#' head(combined_immigration)
#' 
#' tail(combined_immigration)
#' 
#' @export

immigration_fun <-
  function(SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES){
    # White Canada-born
    if_else2(SDCFIMM == 2 & SDCGCBG ==1 & SDCGCGT ==1, 1,
    # Non-white Canadian born   
    if_else2(SDCFIMM == 2 & SDCGCBG ==1 & SDCGCGT ==2, 2,
    # White immigrant born outside of Canada (0-9 years in Canada)
    if_else2(SDCFIMM == 1 & SDCGCBG ==2 & SDCGCGT ==1 & SDCGRES ==1, 3,
    # Non-white immigrant born outside of Canada (0-9 years in Canada)
    if_else2(SDCFIMM == 1 & SDCGCBG ==2 & SDCGCGT ==2 & SDCGRES ==1, 4, 
    # White immigrant born outside of Canada (10+ years in Canada)
    if_else2(SDCFIMM == 1 & SDCGCBG ==2 & SDCGCGT ==1 & SDCGRES ==2, 5,
    # Non-white immigrant born outside of Canada (10+ years in Canada)
    if_else2(SDCFIMM == 1 & SDCGCBG ==2 & SDCGCGT ==2 & SDCGRES ==2, 6,
             
    if_else2(SDCFIMM =="NA(a)"|SDCGCBG =="NA(a)"|SDCGCGT =="NA(a)"
             |SDCGRES =="NA(a)","NA(a)", "NA(b)"
             )))))))
  }