Test a random-effect variance component

test_random_effect() exposes the boundary-aware likelihood-ratio route for random-effect variance components. The v1 certified route is a nested ML comparison that adds exactly one variance parameter and reports the Self-Liang 50:50 mixture reference distribution; a comparison that adds only correlation parameters (e.g. || versus |) is referred to the ordinary chi-square, since a zero correlation is interior to the parameter space (method = "boundary_lrt_ordinary_chisq"). It is intentionally separate from test_effect(), which tests fixed effects.

Usage

test_random_effect(
  fit,
  term,
  method = c("boundary_lrt"),
  refit_for_comparison = c("auto", "error", "ml"),
  ...
)

# S3 method for class 'mm_lmm'
test_random_effect(
  fit,
  term,
  method = c("boundary_lrt"),
  refit_for_comparison = c("auto", "error", "ml"),
  ...
)

Arguments

fit

A fitted mm_lmm.

term

Random-effect term to test. This can be the term id ("r0"), the original random-effect fragment such as "(1 | subject)", or a unique grouping factor name such as "subject".

method

Currently "boundary_lrt".

refit_for_comparison

How to handle REML fits. "auto" and "ml" refit to ML; "error" refuses.

...

Reserved for future methods.

Value

An mm_random_effect_test object with a one-row table.