Permutation for SS-Type-Aligned HDANOVA

Permutation testing for hdanova() objects using SS-type-aligned QR effect matrices. This function is intended as an opt-in alternative to the legacy regression-based permutation() workflow.

Usage

permutation(
  object,
  permute = 1000,
  perm.type = c("approximate", "exact"),
  respect_SStype = NULL,
  unique.digits = 12,
  unique.frac = 0.95,
  exhaustive.warn = TRUE
)

Arguments

object

A hdanova object.

permute

Number of permutations to perform (default = 1000).

perm.type

Type of permutation to perform, either "approximate" or "exact" (default = "approximate").

respect_SStype

Logical or NULL. If NULL (default), use the hdanova object setting (object$more$respect_SStype). If FALSE, follow the legacy regression-based permutation logic. If TRUE, use SS-type-aligned QR contrasts. For REML/ML mixed models, this may yield permutation statistics that differ from fitted-model REML SSQ decompositions selected by REML_ssq_method.

unique.digits

Number of digits used when rounding permutation SSQ values before checking uniqueness (default = 12). Set to NULL to disable this warning.

unique.frac

Minimum fraction of unique rounded SSQ values required to avoid warning (default = 0.95). Set to NULL to disable this warning.

exhaustive.warn

Logical; if TRUE (default), warn when exact permutation uses exhaustive enumeration with fewer permutations than requested.

Value

An updated hdanova object with permute results.

Details

The permutation statistics are computed from SS-type-aligned QR reduced/full model contrasts rather than the legacy regression-based LS matrices. Fixed models and mixed MoM models are supported. Approximate permutation uses a relaxed global shuffle of observations; exact permutation uses permissible block-restricted shuffles. For REML/ML mixed models with respect_SStype = TRUE, a warning is issued to highlight that permutation statistics and fitted-model REML SSQ decompositions are based on different computational definitions.