Run all pairwise order tests

Performs sequential likelihood ratio tests for AD orders 0 vs 1, 1 vs 2, etc.

Usage

run_order_tests_cat(
  y,
  max_order = 2,
  blocks = NULL,
  homogeneous = TRUE,
  n_categories = NULL,
  test = c("lrt", "score", "mlrt", "wald")
)

Arguments

y

Integer matrix of categorical data (n_subjects x n_time).

max_order

Maximum order to test. Default is 2.

blocks

Optional block membership vector.

homogeneous

Whether to use homogeneous parameters across blocks.

n_categories

Number of categories (inferred if NULL).

test

Type of test statistic for each pairwise comparison. One of "lrt" (default), "score", "mlrt", or "wald". Passed to test_order_cat.

Value

A list containing:

tests

List of test_order_cat results for each comparison

table

Summary data frame with all comparisons

fits

List of all fitted models

selected_order

Recommended order based on sequential testing at alpha=0.05

Details

This function performs forward selection: starting from order 0, it tests whether increasing the order provides significant improvement. The selected order is the highest order where the test was significant (at alpha = 0.05).

Examples

if (FALSE) { # \dontrun{
y <- simulate_cat(200, 6, order = 1, n_categories = 2)
result <- run_order_tests_cat(y, max_order = 2)
print(result$table)
cat("Selected order:", result$selected_order, "\n")
} # }