GLMM {lme4} | R Documentation |
Fit a GLMM model with multivariate normal random effects, using Penalized Quasi-Likelihood.
GLMM(formula, family, data, random, ...)
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 .
|
Additional arguments, some of them standard in model-fitting
functions, can be passed to GLMM
.
data
that should be used in the fit. This can be a logical
vector, or a numeric vector indicating which observation numbers are
to be included, or a character vector of the row names to be
included. All observations are included by default."PQL"
, the default, or "Laplace"
.
"PQL"
provides penalized quasi-likelihood estimates.
"Laplace"
provides PQL
estimation followed by optimization of the second-order Laplacian
approximation to the marginal log-likelihood.
NA
s. The default action (na.fail
) causes
lme
to print an error message and terminate if there are any
incomplete observations.lme
.
TRUE
the corresponding
components of the fit (the model frame, the model matrices)
are returned.
An object of class "lme"
: see ssclme-class
.
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.
data(guImmun) fm1 <- GLMM(immun ~ kid2p + mom25p + ord + ethn + momEd + husEd + momWork + rural + pcInd81, family = binomial, data = guImmun, random = ~1|comm) summary(fm1)