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

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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