lmerSummary: Derive VCA-Summary Table from an object fitted via function `lmer`.

Description

This function builds a variance components analysis results table from an object representing a model fitted by lmer of the lme4 R-package. It applies the approximation of the variance-covariance matrix of variance components according to Giesbrecht & Burns (1985) and uses this information to approximate the degrees of freedom according to Satterthwaite (see SAS PROC MIXED documentation option 'CL').

Usage

lmerSummary(obj, VarVC = TRUE, terms = NULL, Mean = NULL, cov = FALSE, X = NULL)

Arguments

obj

(lmerMod) object as returned by function lmer

VarVC

(logical) TRUE = the variance-covariance matrix of variance components will be approximated following the Giesbrecht & Burns approach, FALSE = it will not be approximated

terms

(character) vector, optionally defining the order of variance terms to be used

Mean

(numeric) mean value used for CV-calculation

cov

(logical) TRUE = in case of non-zero covariances a block diagonal matrix will be constructed, FALSE = a diagonal matrix with all off-diagonal element being equal to zero will be contructed

(matrix) design matrix of fixed effects as constructed to meet VCA-package requirements

Value

(list) still a premature 'VCA' object but close to a

Details

This function is not intended to be called directly by users and therefore not exported.

References

Searle, S.R, Casella, G., McCulloch, C.E. (1992), Variance Components, Wiley New York