[R-sig-ME] lmer option nAGQ=0

[Ben Pelzer]

Dear list,

In R version 3.0.3, I recently udated the lme4 package and for a small 
dataset of N=108 pigsties, I ran logistic regression with a random 
intercept across the pigsties. The dependent variable is assumed to be 
binomially distributed, and represents the number of pigs in the sty 
that have a roundworm infection. There is a dichotomous predictor, 
denoting two different types of sty. Using the option nAGQ=0 produces 
PQL estimates. These estimates are, however, quite different from those 
obtained using sas (glimmix), spss (genlinmixed) and glmmPQL in R: these 
three routines produce very similar estimates of the two fixed and the 
one random effect. Now I'm wondering what the reason for the differences 
compared with lmer nAGQ=0 may be. The option to run PQL with lmer may be 
attractive if one has many (complex) models and large datasets, hence my 
questioning. Thanks for any help!!

Ben.