vcovFPC: Obtain finite-population-adjusted variance-covariance matrix

In insight: Easy Access to Model Information for Various Model Objects

Obtain finite-population-adjusted variance-covariance matrix

Description

This function returns the variance-covariance matrix as returned by vcov(), but with finite population correction (FPC) applied.

Usage

vcovFPC(model, ...)

## S3 method for class 'merMod'
vcovFPC(model, population_size = NULL, cluster_size = NULL, kr = FALSE, ...)

Arguments

model	A model inheriting from lm, glm, merMod or glmmTMB (2-level only).
...	Not used.
population_size	The finite population size (for mixed models: for level-1).
cluster_size	The finite population size for level-2 (cluster groups).
kr	Logical, if TRUE, also applies Kenward-Roger adjustment to the returned variance-covariance matrix.

Details

The FPC is defined as:

FPC = \frac{N - n}{N - 1}

FPC for multilevel models is based on the method described by Lai et al. (2018).

Value

The variance-covariance matrix of the fixed effect estimates, as returned by vcov(), but with FPC applied.

References

Lai, M. H., Kwok, O. M., Hsiao, Y. Y., & Cao, Q. (2018). Finite population correction for two-level hierarchical linear models. Psychological methods, 23(1), 94.

insight documentation built on May 21, 2026, 5:06 p.m.