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Add a harmonised gender/sex column to an LFS table

Source: R/lfs_helpers.R
add_lfs_GENDER_SEX.Rd

LFS introduced `GENDER` (with values `"Men+"` / `"Women+"` / `"Non-binary persons"`) to replace the binary `SEX` variable (`"Male"` / `"Female"`) starting in 2020. In any given row exactly one of the two columns is non-`NA`. `add_lfs_GENDER_SEX()` coalesces them into a single harmonised column, recoding `SEX` values to the `GENDER` scale so the result is consistent across all LFS vintages.

Usage

add_lfs_GENDER_SEX(tbl)

Arguments

tbl

A lazy `dplyr::tbl()` returned by [get_pumf()] for an LFS survey, optionally passed through [label_pumf_columns()].

Value

The same lazy table with a new harmonised gender/sex column.

Details

Works on both unlabelled tables (columns `SEX` / `GENDER`, output column named `GENDER_SEX`) and labelled tables produced by [label_pumf_columns()] (columns `"Sex of respondent"` / `"Gender of respondent"`, output column named `"Gender/sex of respondent"`).

The mapping applied to `SEX` / `"Sex of respondent"` when the gender column is `NA`:

  • `"Male"` \(\rightarrow\) `"Men+"`

  • `"Female"` \(\rightarrow\) `"Women+"`

The output column is inserted after `GENDER` / `"Gender of respondent"` when present, or after `SEX` / `"Sex of respondent"` otherwise.

See also

[get_pumf()], [label_pumf_columns()], [add_lfs_SURVDATE()]

Examples

if (FALSE) { # \dontrun{
lfs <- get_pumf("LFS")

# Unlabelled
lfs |> add_lfs_GENDER_SEX() |>
  dplyr::count(SEX, GENDER, GENDER_SEX) |> dplyr::collect()

# Labelled
lfs |> label_pumf_columns() |> add_lfs_GENDER_SEX() |>
  dplyr::count(`Sex of respondent`, `Gender of respondent`,
               `Gender/sex of respondent`) |> dplyr::collect()

close_pumf(lfs)
} # }