Return-Receipt-To: <sis1@NIOBBS1.EM.CDC.GOV>
Encoding: 63 TEXT
X-Mailer: Microsoft Mail V3.0 (beta-2)
Newsgroups: bit.listserv.stat-l
Date:         Thu, 12 Nov 1992 18:11:00 EST
From:         sis1@NIOBBS1.EM.CDC.GOV
Subject:      Categorical data with repeated measures.

Walter R. Pirie writes

> Does anyone know anything that's been done on repeated measures in
> categorical data? It's a problem that occurs fairly often and seems
> difficult to deal with.

The definitive approach, as I have heard from many sources, is Generalized
Estimating Equations (GEE).  The primary references are:

     Liang and Zeger "Longitudinal data analysis using generalized linear
     models" Biometrika (1986):73;13-22.

     Zeger and Liang "Longitudinal Data Analysis for Discrete and Continuous
     Outcomes" Biometrics (1986):42;131-130.

A lot has been published since then, so you might want to check a citation
index.  SPIDA can do this analysis; and macros for GEE are written for S and
for SAS.  The GEE model can handle time-varying covariates very nicely, but
cannot handle large numbers of repeated measures per subject (some of my data
sets have 200 measures per subject).  It can handle unequal numbers of
repeated measures per subject.

Another approach, which is actually better for clustered data than for
repeated measures, is the random effects model.  This includes the
beta-binomial model, which has been known for a long time, and the
normal-logistic model which was developed recently.  This appears to be good
for large number of repeated measures and for unequal numbers of repeated
measures per subject.  I don't think it allows for time varying covariates.
I don't have a reference, but the Egret software package does these analyses.

The CATMOD procedure in SAS (as mentioned by someone else on this list) is a
weighted least squares approach that typically falls apart when there are
small expected counts and/or zero counts.  Also, I don't think this approach
can handle unequal numbers of repeated measures per subject.

Kleinbaum and Kupper give a very nice short course on this subject, and much
of the material I am quoting I learned during the course.  I hope I got it
right.

* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
*  Steve Simon, Mail Stop C-22          *  Delivering on the  *
*  Chief, Statistics Activity           *  nation's promise:  *
*  National Institute for Occupational  *  safety and health  *
*    Safety and Health                  *  at work for all    *
*  4676 Columbia Parkway                *  people...through   *
*  Cincinnati, OH 45226                 *  prevention.        *
*                                       *                     *
*  513-533-8271 (office)                *  NIOSH vision       *
*  513-533-8510 (FAX)                   *  statement          *
* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
*  SMTP gateway to Internet                                   *
*     sis1@niobbs1.em.cdc.gov                                 *
*  X400 gateway to Internet                                   *
*     hhscdc!sis1/o=cdc/ou=cinc/ou=niobbs1@mhs.attmail.com    *
*                                                             *
*  Views expressed here are my own.  Mention of a product or  *
*  company name does not constitute an endorsement by NIOSH.  *
* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *