glmmPQL {MASS}  R Documentation 
Fit a GLMM model with multivariate normal random effects, using Penalized QuasiLikelihood.
glmmPQL(fixed, random, family, data, correlation, weights, control, niter = 10, verbose = TRUE, ...)
fixed 
a twosided linear formula giving fixedeffects part of the model. 
random 
A formula or list of formulae describing the random effects. 
family 
a GLM family. 
data 
an optional data frame used as the first place to find variables in the formulae. 
correlation 
an optional correlation structure. 
weights 
optional case weights as in glm .

control 
an optional argument to be passed to lme .

niter 
maximum number of iterations. 
verbose 
logical: print out record of iterations? 
... 
Further arguments for lme .

glmmPQL
works by repeated calls to lme
, so
package nlme
will be loaded at first use if necessary.
A object of class "lme"
: see lmeObject
.
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 pseudolikelihood approach. Journal of Statistical Computation and Simulation 48, 233–243.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
library(nlme) # will be loaded automatically if omitted summary(glmmPQL(y ~ trt + I(week > 2), random = ~ 1  ID, family = binomial, data = bacteria))