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Impute gender for ambiguous responses

impute_gender.Rd

Imputes gender for persons reporting neither male nor female using Monte Carlo sampling from sample age/gender distribution. Use for cleaning survey data with ambiguous or missing gender.

Usage

impute_gender(
  persons,
  value_labels,
  report_dir = NULL,
  outputs_dir = NULL,
  seed = NULL,
  acs_year = NULL,
  settings
)

Arguments

persons

data.table. Person records to impute.

value_labels

data.table. Value labels for age and gender.

report_dir

character(1), optional. Directory for report output.

outputs_dir

character(1), optional. Directory for imputation output.

seed

integer(1), optional. RNG seed for reproducibility.

acs_year

integer(1), optional. ACS year for reference.

settings

list. Settings object with configs.

Value

data.table. Person IDs and imputed gender.

Details

  • Labels age and gender using value labels.

  • Computes age-by-gender proportions from sample.

  • Fills missing proportions with average share.

  • Assigns gender by Monte Carlo sampling using proportions.

  • Returns data.table with imputed gender for each person.

  • Assumes input is a data.table and value labels are complete.

Settings

  • acs_year (direct): ACS year for reference.

  • rng_seed (direct): random seed for reproducibility.

See also

value_labels

Other imputation utilities: calculate_acs_proportions(), get_acs_ethnicity(), get_acs_race(), get_hh_person_sums(), impute_ethnicity(), impute_income_nonrelatives(), impute_income_pnta(), impute_race(), make_binary(), prep_hhs_for_income_imputation(), prepare_acs_income(), prepare_ethnicity_labels(), prepare_ethnicity_survey_data(), prepare_impute_targets(), prepare_income_fit_dt(), prepare_persons_dt(), update_hh_income_imputed()

Examples

## Not run:
impute_gender(persons, value_labels, seed = 123)
#> Error in impute_gender(persons, value_labels, seed = 123): argument "settings" is missing, with no default