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Re: st: exchanging the outcome and exposure in logistic reg


From   Steven Samuels <[email protected]>
To   [email protected]
Subject   Re: st: exchanging the outcome and exposure in logistic reg
Date   Sun, 25 Jan 2009 19:51:51 -0500

--
Ricardo:

It is correct to do the prospective logistic analysis for unmatched case-control studies. See: Prentice, R. L., & Pyke, R. (1979). Logistic disease incidence models and case-control studies. Biometrika, 66(3), 403-411; Carroll et al., 1995, Journal of the American Statistical Association, 90, 157-169. For matched studies, the appropriate analysis is conditional logistic regression of the case-status on covariates (-clogit-). See: Fleiss, J. L., Levin, B. A., & Paik, M. C. (2003). Statistical methods for rates and proportions (3rd ed ed). Hoboken, N.J: Wiley, 411-416.

-Steve

On Jan 24, 2009, at 1:47 PM, Ricardo Ovaldia wrote:

I recall a discussion on the list a while back regarding this topic, but I did find it in the archives.

In a case-control study the traditional way of modeling a logistic regression is:

logistic case died x1 x2 x3 x4

where case is the presence of cancer (0/1) for example.

Now, an investigator wants me to fit:

logistic died case x1 x2 x3 x4

and I am not sure that this is correct any longer. I recall that it is okay to “flip” the outcome and exposure variables if there are no additional covariates, however, with covariates (x1, x2 …) that is not okay anymore. Is that correct?


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