check_full_blockdiag: Replace a full with a block-diagonal variance covariance...

In JointAI: Joint Analysis and Imputation of Incomplete Data

Replace a full with a block-diagonal variance covariance matrix Check if a full random effects variance covariance matrix is specified for a single variable. In that case, it is identical to a block-diagonal matrix. Change the rd_vcov specification to blockdiag for clarity (because then the variable name is used in the name of b, D, invD, ...)

Description

Replace a full with a block-diagonal variance covariance matrix Check if a full random effects variance covariance matrix is specified for a single variable. In that case, it is identical to a block-diagonal matrix. Change the rd_vcov specification to blockdiag for clarity (because then the variable name is used in the name of b, D, invD, ...)

Usage

check_full_blockdiag(rd_vcov)

Arguments

rd_vcov

a valid random effects variance-covariance structure specification (i.e., checked using expand_rd_vcov_full())

Value

a valid random effects variance-covariance structure specification

JointAI documentation built on April 27, 2023, 5:15 p.m.