mc_anova_disp: Wald Tests for Dispersion Components

In mcglm: Multivariate Covariance Generalized Linear Models

Wald Tests for Dispersion Components

Description

Performs Wald chi-square tests for dispersion (covariance) parameters by response variable in multivariate covariance generalized linear models fitted with mcglm. This function is intended for joint hypothesis testing of dispersion coefficients associated with categorical covariates with more than two levels. It is not designed for model comparison.

Usage

mc_anova_disp(object, idx_list, names_list, ...)

Arguments

object	An object of class "mcglm", typically the result of a call to mcglm.
idx_list	A list of integer vectors indexing dispersion parameters to be jointly tested for each response.
names_list	A list of character vectors with covariate names to be displayed in the output tables.
...	Currently not used.

Value

The object is a list of data frames, one per response variable. Each data frame contains the following columns:

Covariate

Name of the covariate associated with the dispersion parameters being tested.

Chi.Square

Wald chi-square test statistic.

Df

Degrees of freedom of the test.

p.value

P-value associated with the chi-square test.

See Also

mcglm, vcov, coef

mcglm documentation built on Jan. 9, 2026, 1:07 a.m.