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Prepare household vehicles target variable for weighting

prep_target_vehicles.Rd

Creates a standardized household vehicles target variable for household-level weighting and expansion, using either PUMS or survey input. Use when preparing vehicles targets for synthetic population or survey analysis.

Usage

prep_target_vehicles(
  h_data,
  p_data,
  target_name = "h_vehicles",
  codebook,
  settings
)

Arguments

h_data

data.table. Household-level input. Required columns:

  • For PUMS: must include SERIALNO, VEH.

  • For survey: must include vehicle and adult columns as specified in settings. Rows: one per household. Modified by reference: no (returns copy).

p_data

data.table. Person-level input. Required columns:

  • For PUMS: must include SERIALNO, AGEP.

  • For survey: must include age column as specified in settings. Rows: one per person. Modified by reference: no (returns copy).

target_name

character(1). Name of the target variable to create (default: "h_vehicles").

codebook

data.table. Codebook for variable mapping; must include age and vehicle value and label columns.

settings

list. Project settings; must include targets[[target_name]] with levels, pums_input, and survey_input.

Value

data.table. Copy of household-level input with new target variable column (target_name).

  • Columns: all original plus target_name (factor)

  • Values: "none", "insuff", "suff"

  • Row order preserved

Details

  • Detects input type (PUMS vs. survey) by presence of SERIALNO column in h_data.

  • For PUMS:

    • Uses VEH and VEH_label columns for vehicle count and label.

    • Aggregates number of adults from person-level data (AGEP >= 16).

  • For survey:

    • Uses codebook to identify adults using regex str_detect(label, '16[- ]17') (default survey value: 995 for missing/work from home).

    • Aggregates number of adults and vehicles per household.

  • Applies logic:

    • num_vehicles == 0 → "none"

    • num_vehicles < num_adults → "insuff"

    • num_vehicles >= num_adults → "suff"

  • Applies cut_and_label to bin vehicle sufficiency into target levels.

  • Renames output column to target_name (default: h_vehicles).

  • Returns a copy of the input data.table with the new target variable.

  • Error handling: stops if levels do not match expected values.

Settings

  • targets[["h_vehicles"]] (direct): must include levels, pums_input, and survey_input.

See also

get_target_methods, prep_target_h_size, prep_target_workers

Other target preparation: get_target_methods(), prep_target_adults(), prep_target_age(), prep_target_commutemode(), prep_target_cross(), prep_target_edulevel(), prep_target_employment(), prep_target_ethnicity(), prep_target_gender(), prep_target_h_size(), prep_target_income(), prep_target_kids(), prep_target_race(), prep_target_univstudent(), prep_target_workers(), prep_transit_target(), prepare_targets(), run_tabulate_method()

Examples

## Not run:
prep_target_vehicles(h_data, p_data, target_name = "h_vehicles", codebook, settings)
#> Error: object 'h_data' not found
## End(Not run)