Likelihood-ratio test for genetic covariance structure — covariance_structure

Usage

covariance_structure_lrt(constrained, full, ...)

Arguments

constrained, full: Two hsquared_fit objects from the multivariate model; full must nest constrained (more genetic covariance parameters).
...: Unused.

Value

A one-row data frame with statistic, df, pvalue, boundary, and the constrained / full genetic-structure labels.

Details

covariance_structure_lrt(constrained, full) is an experimental nested likelihood-ratio test comparing two multivariate fits on the same data: a constrained genetic structure (currently genetic_structure = "diagonal") against the full "unstructured" fit. The statistic is 2 * (logLik(full) - logLik(constrained)) on df = n_genetic_params(full) - n_genetic_params(constrained).

For diagonal-vs-unstructured the null (off-diagonal genetic covariances = 0) is interior, so the chi^2 reference is exact (boundary = FALSE). Structures whose null lies on a rank/PSD boundary (low-rank / factor-analytic) would need a chi^2-mixture correction and are gated out of the R bridge for now.

It mirrors the engine multivariate REML validation row (partial): asymptotic, REML-only, dense validation-scale, with the multivariate recovery calibration not yet passed – a reported test, not a validated one. Both fits must be on the same response, fixed effects, and pedigree, and both must have converged. The function refuses mismatched fits. A negative statistic or a comparison whose null is on a boundary produces a warning and an NA p-value rather than a misleading chi-square result.