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Re: st: Converting an odds ratio in a risk ratio - Logit


From   Svend Juul <SJ@SOCI.AU.DK>
To   <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Converting an odds ratio in a risk ratio - Logit
Date   Sun, 15 Jun 2008 09:41:15 +0200

Leda Inga wrote:
 
I ran a logit with diferent dummies as you can see below:
 
Y = f(X, D1_3, D4, D5, .., D10, D_more10)
 
X: set of regressors
 
D_: dummies that classify each indiviual by the number of visits made
to the doctor.
 
Since I ran a fixed effect logit, I only can get the odds ratio of
each dummy. Nevertheless, I would like to convert them in risk ratios.
I hope that someone has any idea or has been in a similar situation
before.
 
According to the recomendation of Jun Zhang and Kai F. Yu
(http://jama.ama-assn.org/cgi/content/full/280/19/1690#ACK) it can be
used the following:
 
RR= OR/ (1 - Po + Po*OR)
 
where Po is the incidence of Y in the "unexposed group".
 
Since I used diferent dummies, I'm not sure what should be my
"unexposed group" for each dummy. I know that the coefficient of each
dummy must be interpreted versus the reference group (in my case, zero
visits). But maybe to get the risk ratios of "X" visits versus the
reference (zero visits) the unexposed group should be "X-1" visits or
all but "X" (since each dummy takes values of zero for all individuals
who didn't have "X" visits)
 
============================================================
 
   findit relative risk
led me to an excellent FAQ about it at
   http://www.ats.ucla.edu/stat/stata/faq/relative_risk.htm
 
It shows the use of -glm-. Alternatively, you can use -binreg- with
the -rr- option to obtain relative risks.
 
Joseph Hilbe made the -oddsrisk- command; it uses the method described
by Zhang and Yu. Find it by:
   findit oddsrisk
 
The second question is about the choice of reference group. In my
world (epidemiology), I don't think there is much doubt. The non-
visitors is a natural reference group, and it should be the reference
for each of the other exposure levels. Shifting reference groups
makes the results quite difficult to interpret.
 
Hope this helps
Svend

________________________________________________________ 
 
Svend Juul
Institut for Folkesundhed, Afdeling for Epidemiologi
(Institute of Public Health, Department of Epidemiology)
Vennelyst Boulevard 6 
DK-8000 Aarhus C,  Denmark 
Phone, work:   +45 8942 6090 
Phone, home:   +45 8693 7796 
Fax:           +45 8613 1580 
E-mail:        sj@soci.au.dk 
_________________________________________________________ 

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