scf (version 1.0.5)

scf_xtab: Cross-Tabulate Two Discrete Variables in Multiply-Imputed SCF Data

Description

Computes replicate-weighted two-way cross-tabulations of two discrete variables using multiply-imputed SCF data. Estimates cell proportions and standard errors, with optional scaling of proportions by cell, row, or column. Results are pooled across implicates using Rubin's Rules.

Usage

scf_xtab(scf, rowvar, colvar, scale = "cell")

Value

A list of class "scf_xtab" with:

results

Data frame with one row per cell. Columns: row, col, prop, se, row_share, col_share, rowvar, and colvar.

matrices

List of matrices: cell (default proportions), row, col, and se.

imps

List of implicate-level cell count tables.

aux

List with rowvar and colvar names.

Arguments

scf

A scf_mi_survey object, typically created by scf_load(). Must include five implicates with replicate weights.

rowvar

A one-sided formula specifying the row variable (e.g., ~edcl).

colvar

A one-sided formula specifying the column variable (e.g., ~racecl).

scale

Character. Proportion basis: "cell" (default), "row", or "col".

Statistical Notes

Implicate-level tables are created using svytable() on replicate-weighted designs. Proportions are calculated as shares of total population estimates. Variance across implicates is used to estimate uncertainty. Rubin's Rules are applied in simplified form.

For technical details on pooling logic, see scf_MIcombine() or the SCF package manual.

Examples

# Do not implement these lines in real analysis:
# Use functions `scf_download()` and `scf_load()`
td <- tempfile("xtab_")
dir.create(td)

src <- system.file("extdata", "scf2022_mock_raw.rds", package = "scf")
file.copy(src, file.path(td, "scf2022.rds"), overwrite = TRUE)
scf2022 <- scf_load(2022, data_directory = td)

# Example for real analysis: Cross-tabulate ownership by education
scf_xtab(scf2022, ~own, ~edcl, scale = "row")

# Do not implement these lines in real analysis: Cleanup for package check
unlink(file.path(td, "scf2022.rds"), force = TRUE)