|From||VISINTAINER PAUL <PAUL_VISINTAINER@nymc.edu>|
|Subject||st: RE: clogit or logistic for matched pairs|
|Date||Thu, 6 Nov 2003 13:58:06 -0500|
If I understand your description of the study, Michael, you don't have a case-control study, but rather a matched cohort study, (e.g., exposed twin vs. unexposed twin). -clogit- would work for you in the usual sense, unless you regressed exposure status on disease. You might want to try -xtlogit- which will take into account the clustering of your independent exposure variable. This will satisfy your need for a conditional approach. Depending on your data and the covariates you include, you may actually get an outcome that is quite close to -logit- with a robust option.
From: firstname.lastname@example.org [mailto:email@example.com] On Behalf Of Michael Ingre
Sent: Thursday, November 06, 2003 11:01 AM
Subject: st: clogit or logistic for matched pairs
I want to estimate the risk for an exposed twin to develop a symptom
relative an unexposed twin. I have 169 pairs of monozygotic twins that are
discordant on my exposure variable. The basic design is a case (exposed) -
control (unexposed) study. The outcome variable (symptom) is binary coded.
The most obvious method should be -clogit- however, I'm not satisfied with
Like McNemar, it excludes the ties between cases and controls and the odds
ratio returned describes the ratio of cases "winning" over controls.
However, I would like to estimate the ratio of a case to HAVE the symptom
(not "winning") compared to the control.
I have been criticized for using logistic regression with the cluster option
and robust variance estimator. My OR is said to be invalid.
Actually, the criticism is harder than that: My analyses is said to be
. logistic dv iv , cluster(twinpairid)
Do you have any advice?
Thanks in advance
Department of Psychology
Stockholm University &
National Institute for
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