nested mixed effects logistic regression binomial glm)results differ by function.

I have a dichotomous outcome on 2500 individuals. From 18 geographical
areas, and many households nested within areas. I need to assess the
association between various predictors and my outcome, adjusting for the
correlation within households, as well as within areas. The following R
functions provide dramatically different results.

glmer(CC~predictor+1|area/household,family=binomial)
glmmPQL(CC~predictor, random=~1|area/household),family=binomial)

PQL is known to be biased, the amount depending on a few things including 
the proportion CC in the sample, and number of levels for the REs. You 
could try hglm (package hglm, using EQL) and see how different the results 
are from that ;)  It is also possible one or both programs encountered 
numerical problems because of features of your data. If you can send your 
original data, or simulated data of the same structure (that gives a 
similar problem!), we could have a look.

Cheers, David.

| David Duffy (MBBS PhD)
| email: David.Duffy at qimrberghofer.edu.au  ph: INT+61+7+3362-0217 fax: -0101
| Genetic Epidemiology, QIMR Berghofer Institute of Medical Research
| 300 Herston Rd, Brisbane, Queensland 4006, Australia  GPG 4D0B994A