Re: [R] R package that has (much) the same capabilities as SAS v9 PROC GENMOD

From: Simon Blomberg <Simon.Blomberg_at_anu.edu.au>
Date: Tue 05 Apr 2005 - 12:20:10 EST

The questioner clearly wants generalized linear mixed models. lmer in package lme4 may be more appropriate. (Prof. Bates is a co-author.). glmmPQL should do the same job, though, but with less accuracy.

Simon.

>check glm()
>
>On Apr 4, 2005 6:46 PM, William M. Grove <grove001@umn.edu> wrote:
>> I need capabilities, for my data analysis, like the Pinheiro & Bates
>> S-Plus/R package nlme() but with binomial family and logit link.
>>
>> I need multiple crossed, possibly interacting fixed effects (age cohort of
>> twin when entered study, sex of twin, sampling method used to acquire twin
>> pair, and twin zygosity), a couple of random effects other than the cluster
>> variable, and the ability to have a variable of the sort that P&B call
>> "outer" to the clustering variable---zygosity. Dependent variables are all
>> parental (mom, dad separately of course) psychiatric diagnoses.
>>
>> In my data, twin pair ID is the clustering variable; correlations are
>> expected to be exchangeable but substantially different between members of
>> monozygotic twin pairs and members of dizygotic twin pairs. Hence, in my
>> analyses, the variable that's "outer" to twin pair is monozygotic vs.
>> dizygotic which of course applies to the whole pair.
>>
>> nlme() does all that but requires quasi-continuous responses, according to
>> the preface/intro of P&B's mixed models book and what I infer from online
>> help (i.e., no family= or link= argument).
>>
>> The repeated() library by Lindsey seems to handle just one nested random
>> effect, or so I believe I read while scanning backlogs of the R-Help list.
>>
>> glmmPQL() is in the ballpark of what I need, but once again seems to lack
>> the "outer" variable specification that nlme() has, and which PROC GENMOD
>> also has---and which I need.
>>
>> I read someplace of yags() that apparently uses GEE to estimate parameters
>> of nonlinear models including GLIMs/mixed models, just the way PROC GENMOD
>> (and many another program) does. But on trying to install it (either
>> v4.0-1.zip or v4.0-2.tar.gz from Carey's site, or Ripley's Windows port)
>> from a local, downloaded zip file (or tar.gz file converted to zip file), I
>> always get an error saying:
>> > Error in file(file, "r") : unable to open connection
>> > In addition: Warning message:
>> > cannot open file `YAGS/DESCRIPTION'
>> with no obvious solution.
>>
>> So I can't really try it out to see if it does what I want.
>>
>> You may ask: Why not just use GENMOD and skip the R hassles? Because I
>> want to embed the GLIM/mixed model analysis in a stratified resampling
>> bootstrapping loop. Very easy to implement in R, moderately painful to do
>> in SAS.
>>
>> Can anybody give me a lead, or some guidance, about getting this job done
>> in R? Thanks in advance for your help.
>>
>> Regards,
>>
>> Will Grove | Iohannes Paulus PP. II, xxx
>> Psychology Dept. |
>> U. of Minnesota |
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>
>
>--
>WenSui Liu, MS MA
>Senior Decision Support Analyst
>Division of Health Policy and Clinical Effectiveness
>Cincinnati Children Hospital Medical Center
>
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-- 
Simon Blomberg, B.Sc.(Hons.), Ph.D, M.App.Stat.
Visiting Fellow
School of Botany & Zoology
The Australian National University
Canberra ACT 0200
Australia

T: +61 2 6125 8057  email: Simon.Blomberg@anu.edu.au
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Received on Tue Apr 05 12:27:39 2005

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