Immigration by ethnicity and settlement

Source: R/immigration.R

This function creates a categorical variable based on immigrant status (SDCFIMM), country of birth (SDCGCBG), ethnicity (SDCGCGT), and time in Canada (SDCGRES).

immigration_fun(SDCFIMM, SDCGCBG, SDCGCGT, SDCGRES)

Arguments

SDCFIMM

Immigrant status (1-immigrant, 2-non-immigrant)
SDCGCBG

Country of birth (1-Canada, 2-Outside of Canada)
SDCGCGT

Cultural or racial origin (1-white, 2-visible minority)
SDCGRES

Length/time in Canada since immigration (1- 0-9 years, 2- 10+ years)

Value

Categorical variable (immigration_der) with six categories:

  • 1 - White Canada-born

  • 2 - Non-white Canadian born

  • 3 - White immigrant born outside of Canada (0-9 years in Canada)

  • 4 - Non-white immigrant born outside of Canada (0-9 years in Canada)

  • 5 - White immigrant born outside of Canada (10+ years in Canada)

  • 6 - Non-white immigrant born outside of Canada (10+ years in Canada)

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.

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"
  )
)

#> No variable_details detected.
#>               Loading cchsflow variable_details
#> Using the passed data variable name as database_name
#> NOTE for SDCGCBG: CCHS 2001 does not have don't know (7) or refusal (8)
#> NOTE for SDCGCGT: CCHS 2001 missing don't know (7), refusal (8)
#> NOTE for SDCGRES: CCHS 2001 missing don't know (7), refusal (8)

head(immigration2001)

#>   SDCFIMM SDCGCBG SDCGCGT SDCGRES immigration_der
#> 1       2       1       1   NA(a)               1
#> 2       2       1       1   NA(a)               1
#> 3       1       2       1       1               3
#> 4       2       1       1   NA(a)               1
#> 5       2       1       1   NA(a)               1
#> 6       2       1       1   NA(a)               1

immigration2009_2010 <- rec_with_table(
  cchs2009_2010_p, c(
    "SDCFIMM", "SDCGCBG", "SDCGCGT", "SDCGRES", "immigration_der"
  )
)

#> No variable_details detected.
#>               Loading cchsflow variable_details
#> Using the passed data variable name as database_name
#> NOTE for SDCGCBG: CCHS 2001 does not have don't know (7) or refusal (8)
#> NOTE for SDCGCGT: CCHS 2001 missing don't know (7), refusal (8)
#> NOTE for SDCGRES: CCHS 2001 missing don't know (7), refusal (8)

tail(immigration2009_2010)

#>     SDCFIMM SDCGCBG SDCGCGT SDCGRES immigration_der
#> 195       2       1       1   NA(a)               1
#> 196       2       1       1   NA(a)               1
#> 197       2       1       1   NA(a)               1
#> 198       2       1       2   NA(a)               2
#> 199       2       1       1   NA(a)               1
#> 200       1       2       1       2               5

combined_immigration <- merge_rec_data(immigration2001, immigration2009_2010)

head(combined_immigration)

#>   SDCFIMM SDCGCBG SDCGCGT SDCGRES immigration_der
#> 1       2       1       1   NA(a)               1
#> 2       2       1       1   NA(a)               1
#> 3       1       2       1       1               3
#> 4       2       1       1   NA(a)               1
#> 5       2       1       1   NA(a)               1
#> 6       2       1       1   NA(a)               1

tail(combined_immigration)

#>     SDCFIMM SDCGCBG SDCGCGT SDCGRES immigration_der
#> 395       2       1       1   NA(a)               1
#> 396       2       1       1   NA(a)               1
#> 397       2       1       1   NA(a)               1
#> 398       2       1       2   NA(a)               2
#> 399       2       1       1   NA(a)               1
#> 400       1       2       1       2               5