# GLMM

##### Fit Generalized Linear Mixed Models via PQL

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

- Keywords
- models

##### Usage

`GLMM(formula, family, data, random, ...)`

##### Arguments

- formula
- a two-sided linear model formula giving fixed-effects part of the model.
- family
- a GLM family, see
`glm`

. - data
- an optional data frame used as the first place to find variables in the formulae.
- random
- A formula or named list of formulae describing the random effects.
- ...
- Optional further arguments such as
`subset`

and`na.action`

.

##### Details

Additional arguments, some of them standard in model-fitting
functions, can be passed to `GLMM`

.
[object Object],[object Object],[object Object],[object Object],[object Object]

##### Value

- An object of class
`"lme"`

: see`ssclme-class`

.

##### synopsis

GLMM(formula, family, data, random, method = c("PQL", "Laplace"), control = list(), subset, weights, na.action, offset, model = TRUE, x = FALSE, y = FALSE, ...)

##### 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

##### Examples

```
data(guImmun)
fm1 <-
GLMM(immun ~ kid2p + mom25p + ord + ethn +
momEd + husEd + momWork + rural + pcInd81,
family = binomial, data = guImmun, random = ~1|comm)
summary(fm1)
```

*Documentation reproduced from package lme4, version 0.6-6, License: GPL version 2 or later*