lme4 (version 0.4-3)

GLMM: Fit Generalized Linear Mixed Models via PQL

Description

Fit a GLMM model with multivariate normal random effects, using Penalized Quasi-Likelihood.

Usage

GLMM(formula, family, data, random, control, niter, method, verbose, ...)

Arguments

formula
a two-sided linear model formula giving fixed-effects part of the model.
family
a GLM family, see glm.
random
A formula or list of formulae describing the random effects.
data
an optional data frame used as the first place to find variables in the formulae.
control
an optional argument to be passed to lme.
niter
maximum number of PQL iterations. Default is 20.
method
character: Estimation method to be used. Possible values are "PQL", the default, or "Laplace". "PQL" provides penalized quasi-likelihood estimates. "Laplace" provides PQL estimation foll
verbose
logical: print out record of iterations? Default is FALSE.
...
Optional further arguments such as subset and na.action.

Value

References

Schall, R. (1991) Estimation in generalized linear models with random effects. Biometrika 78, 719--727.

Breslow, N. E. and Clayton, D. G. (1993) Approximate inference in generalized linear mixed models. Journal of the American Statistical Association 88, 9--25.

Wolfinger, R. and O'Connell, M. (1993) Generalized linear mixed models: a pseudo-likelihood approach. Journal of Statistical Computation and Simulation 48, 233--243.

See Also

lme

Examples

Run this code
library(lme4)
data(guImmun)
fm1 = GLMM(immun ~ kid2p + mom25p + ord + ethn +
                  momEd + husEd + momWork + rural + pcInd81,
          data = guImmun, family = binomial,
          random = ~1|comm/mom)
summary(fm1)
fm2 = GLMM(immun ~ kid2p + mom25p + ord + ethn +
                  momEd + husEd + momWork + rural + pcInd81,
          data = guImmun, family = binomial,
          random = ~1|comm, method = 'Laplace')
summary(fm2)

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