[R] glmmPQL questions

From: JEB Halliday <s0454869_at_sms.ed.ac.uk>
Date: Mon 28 Mar 2005 - 21:06:25 EST

I am looking a risk factors for disease in cattle and am interested in modelling farm and sampling cluster as random effects (My outcome is positive or negative at the level of the farm). I am using R version 2.0.1 on a Mac and have identified glmmPQL as hopefully the correct function to use. I have run a couple of models using this but was hoping that you might be able to answer a few questions.

e.g. model<-glmmPQL(farmstatus~cattlenumber,random~1|farm,binomial)

I am pretty new to both R and stats so if these questions are very simple and I am just missing something, suggestions about good texts on GLMM in R would be great.

First up, what is the best way to constrain the model to only look at certain levels of a multi-level factor e.g. a categorisation of cattle number where all points of high influence

(as determined using: summary(influence.measures(model)) )

are confined to the largest class (D) and I want to run the model which just looks at levels A,B and C? (or only months May-September..)

I was also wondering about the best way to force specified variables to remain in the model when running e.g. stepwise selection of interaction terms?

Finally, is there is a recognised method for dealing with missing values in these models?
and as a minor point the models do not run unless i specify the data= part of the syntax and as this is apparently an optional piece of information I was wondering why this is required when all of my variables are in the same data frame (and even when this data frame is attached?)

Any help would be greatly appreciated

Jo Halliday
MSc student
University of Edinburgh
s0454869@sms.ed.ac.uk



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