se: Standard Error

In glmm: Generalized Linear Mixed Models via Monte Carlo Likelihood Approximation

Standard Error

Description

A function that calculates the standard error for the Monte Carlo maximum likelihood estimates returned from glmm.

Usage

se(object)

Arguments

object

An object of class glmm usually created using glmm.

Details

With maximum likelihood performed by Monte Carlo likelihood approximation, there are two sources of variability: there is variability from sample to sample and from Monte Carlo sample (of generated random effects) to Monte Carlo sample. The first source of variability (from sample to sample) is measured using standard error, which appears with the point estimates in the summary tables. The second source of variability is due to the Monte Carlo randomness, and this is measured by the Monte Carlo standard error.

Value

se	The standard errors for the Monte Carlo maximum likelihood estimates returned from glmm

Author(s)

Christina Knudson

See Also

glmm for model fitting.

mcse for calculating Monte Carlo standard error.

Examples

library(glmm)
data(BoothHobert)
set.seed(1234)
mod <- glmm(y~0+x1, list(y~0+z1), varcomps.names=c("z1"), 
data=BoothHobert, family.glmm=bernoulli.glmm, m=100, doPQL=TRUE)

se(mod)

glmm documentation built on Sept. 30, 2024, 9:44 a.m.