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st: Re: clogit or logistic for matched pairs
At 17:01 06/11/03 +0100, Michael Ingre wrote:
I do not know your supervisor. However, if you want a risk ratio instead of
an odds ratio, and you want to cluster the standard errors by twin pair,
then you should use -glm- to fit a model with log link and binomial error.
I would type
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?
gene byte baseline=1
glm dv iv baseline, link(log) family(binomial) cluster(twinpairid) eform
and the parameter -baseline- will be a risk for the unexposed twin, and the
parameter -iv- will be a risk ratio.
The reason for defining the variable -baseline- and using the -noconst-
option is that, otherwise, the -eform- option causes Stata not to print the
intercept parameter -_cons-. We therefore need to define -baseline- as an
X-variable and tell Stata that there is no intercept for it to hide from us.
I hope this helps.
Lecturer in Medical Statistics
Department of Public Health Sciences
King's College London
5th Floor, Capital House
42 Weston Street
London SE1 3QD
Tel: 020 7848 6648 International +44 20 7848 6648
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or 020 7848 6605 International +44 20 7848 6605
Opinions expressed are those of the author, not the institution.
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