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

Ben Pelzer b.pelzer at maw.ru.nl
Fri Mar 21 12:13:36 CET 2014

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!!


More information about the R-sig-mixed-models mailing list