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

[Simon Blomberg]

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 at 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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>>  xxx <br>
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>>  U. of Minnesota&nbsp; |<br>
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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 at anu.edu.au
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