R help - Mar 2008 - package for repeated measures ANOVA with various link functions

R 2.6.0
Windows XP

At the risk of raising the ire of the R gods . . .
I am looking for a package that will allow me to perform a poisson,
quasipoisson, or negative binomial regression with adjustment for repeated
measures. I have looked at glm, it does not appear to allow repeated measures.
Although I can't get any help for lme or lme4 I remember that those packages
perform repeated measures using random effects, not repeated measures ANOVA
which is what I am looking for. (By the why, how can I get help for lme4? I have
tried ?lme4, help.search("lme4") etc. to no avail.)
A suggestion for a package that will allow for repeated measures ANOVA in the
context of various link functions would be appreciated.
Thanks as always,
John  

John Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)

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> -----Original Message-----
> From: r-help-bounces at r-project.org 
> [mailto:r-help-bounces at r-project.org] On Behalf Of John Sorkin
> Sent: Tuesday, March 04, 2008 8:52 AM
> To: r-help at r-project.org
> Subject: [R] package for repeated measures ANOVA with various 
> link functions
> 
> R 2.6.0
> Windows XP
> 
> At the risk of raising the ire of the R gods . . .
> I am looking for a package that will allow me to perform a 
> poisson, quasipoisson, or negative binomial regression with 
> adjustment for repeated measures. I have looked at glm, it 
> does not appear to allow repeated measures. Although I can't 
> get any help for lme or lme4 I remember that those packages 
> perform repeated measures using random effects, not repeated 
> measures ANOVA which is what I am looking for. (By the why, 
> how can I get help for lme4? I have tried ?lme4, 
> help.search("lme4") etc. to no avail.)
> A suggestion for a package that will allow for repeated 
> measures ANOVA in the context of various link functions would 
> be appreciated.
> Thanks as always,
> John  
> 
John,

If you install the packages, help files will be installed along with them.  If
you don't want to install first, go to

http://cran.r-project.org/

And select packages under software on the left hand side of the screen.  You
will be able to look at some documentation there, e.g. there is a manual for
lme4 available.

Hope this is helpful,

Dan


Daniel J. Nordlund
Research and Data Analysis
Washington State Department of Social and Health Services
Olympia, WA  98504-5204

On Tue, Mar 4, 2008 at 10:52 AM, John Sorkin
<jsorkin at grecc.umaryland.edu> wrote:
> R 2.6.0
>  Windows XP
>  At the risk of raising the ire of the R gods . . .
>  I am looking for a package that will allow me to perform a poisson,
quasipoisson, or negative binomial regression with adjustment for repeated
measures. I have looked at glm, it does not appear to allow repeated measures.
Although I can't get any help for lme or lme4 I remember that those packages
perform repeated measures using random effects, not repeated measures ANOVA
which is what I am looking for. (By the why, how can I get help for lme4? I have
tried ?lme4, help.search("lme4") etc. to no avail.)
>  A suggestion for a package that will allow for repeated measures ANOVA in
the context of various link functions would be appreciated.
I think you would need to be more specific about the model than just
saying "repeated measures ANOVA".  To me, "repeated
measures"
describes a structure in the data.  There are many ways that one could
model the effects of the repeated measures; some might make sense in
the context of your data and some might not.  Without further details
about how you want to model the effect of the repeated measurements it
would be difficult to say if you could use the lmer function in the
lme4 package to do so.

The purpose of the S language and the R implementation of that
language is to facilitate exploration of data, including the fitting
of models that may be appropriate - always keeping in mind George
Box's famous statement that, "All models are wrong, but some models
are useful".  The "one size fits all" approach to data analysis -
also
known as "give me a quart and a half of statistics and just make sure
that there is a p-value less than 5% somewhere in there" - doesn't fit
well into the R system.