effects: Mixed Effects

In mbest: Moment-Based Estimation for Hierarchical Models

Description

Get the fixed effects, random effect variances, and empirical Bayes random effect estimates.

Usage

## S3 method for class 'mhglm'
fixef(object, ...)

## S3 method for class 'mhglm'
ranef(object, condVar = FALSE, ...) 

## S3 method for class 'mhglm'
vcov(object, ...)

## S3 method for class 'mhglm'
VarCorr(x, sigma = 1, ...)

## S3 method for class 'mhglm_ml'
fixef(object, ...)

## S3 method for class 'mhglm_ml'
ranef(object, condVar = FALSE, ...) 

## S3 method for class 'mhglm_ml'
vcov(object, ...)

## S3 method for class 'mhglm_ml'
VarCorr(x, sigma = 1, ...)

Arguments

object, x	an mhglm object.
sigma	a factor by which to scale the random effect variance-covariance matrix.
condVar	a logical indicating whether conditional covariance matrices for the random effects should be returned.
...	further arguments passed to or from other methods.

Details

fixef returnes the fixed effects, while vcov returns the variance-covariance matrix of the fixed effect estimates.

VarCorr returns the random effect covariance matrix. ranef returns the empirical Bayes random effect estimates.

These functions behave like their counterparts in the nlme package.

See Also

fixef, ranef, VarCorr, from package nlme.

mbest documentation built on May 2, 2019, 2:14 p.m.