Plot Chi-Square Tests for Categorical Associations (optionally stratified by covariates)

Conducts Chi-square tests between sets of categorical variables and visualizes the results. NOTE: Chi-square tests do not natively "adjust" for covariates. If covars are provided, this function can (optionally) run tests within strata (each combination of covariate levels), and combine p-values across strata (Fisher's method) for a single summary p-value per pair. If you need true covariate adjustment, use regression-based models (logistic/multinomial).

Usage

PlotChiSqCovar(
  Data,
  xVars,
  yVars,
  covars = NULL,
  Relabel = TRUE,
  Ordinal = TRUE,
  min_n = 4
)

Arguments

Data

A data.frame containing the dataset.

xVars

Character vector of x-axis categorical variables.

yVars

Character vector of y-axis categorical variables. If NULL, uses xVars.

covars

Optional character vector of covariate variables used for stratification (not adjustment).

Relabel

Logical; whether to use variable labels (sjlabelled) in the plot.

Ordinal

Logical; included for backward compatibility (currently unused here).

min_n

Minimum number of complete observations required for a tested association.

Value

A list with:

p

ggplot for unadjusted p-values

pvaltable

wide table of unadjusted p-values

p_FDR

ggplot for FDR-adjusted p-values

pvaltable_FDR

wide table of FDR-adjusted p-values

details

long table with diagnostics (n, warnings, strata info)