lme4 (version 1.1-7)

VarCorr: Extract Variance and Correlation Components

Description

This function calculates the estimated variances, standard deviations, and correlations between the random-effects terms in a mixed-effects model, of class merMod (linear, generalized or nonlinear). The within-group error variance and standard deviation are also calculated.

Usage

## S3 method for class 'merMod':
VarCorr(x, sigma=1, rdig=3)
## S3 method for class 'VarCorr.merMod':
as.data.frame(x, row.names = NULL, optional =
FALSE, ...)

Arguments

x

for VarCorr: a fitted model object, usually an object inheriting from class merMod. For as.data.frame, a VarCorr.merMod object returned from VarCorr.

sigma

an optional numeric value used as a multiplier for the standard deviations.

rdig

an optional integer value specifying the number of digits used to represent correlation estimates.

row.names

Ignored: necessary for the as.data.frame method.

optional

Ignored: necessary for the as.data.frame method.

...

Ignored: necessary for the as.data.frame method.

Value

• An object of class VarCorr.merMod. The internal structure of the object is a list of matrices, one for each random effects grouping term. For each grouping term, the standard deviations and correlation matrices for each grouping term are stored as attributes "stddev" and "correlation", respectively, of the variance-covariance matrix, and the residual standard deviation is stored as attribute "sc" (for glmer fits, this attribute stores the scale parameter of the model).

  The as.data.frame method produces a combined data frame with one row for each variance or covariance parameter (and a row for the residual error term where applicable) and the following columns: [object Object],[object Object],[object Object],[object Object],[object Object]

Details

The print method for VarCorr.merMod objects has optional arguments digits (specify digits of precision for printing) and comp: the latter is a character vector with any combination of "Variance" and "Std.Dev.", to specify whether variances, standard deviations, or both should be printed.

See Also

lmer, nlmer

Examples

data(Orthodont, package="nlme")
fm1 <- lmer(distance ~ age + (age|Subject), data = Orthodont)
(vc <- VarCorr(fm1))  ## default print method: standard dev and corr
## both variance and std.dev.
print(vc,comp=c("Variance","Std.Dev."),digits=2)
## variance only
print(vc,comp=c("Variance"))
as.data.frame(vc)