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Re: st: RRR with CI from logit model


From   Constantine Daskalakis <C_Daskalakis@mail.jci.tju.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RRR with CI from logit model
Date   Tue, 02 Nov 2004 13:09:22 -0500

At 12:42 PM 11/2/2004, Michael Ingre wrote:
On 2004-11-02, at 18.19, Constantine Daskalakis wrote:

Look at the estimates and estimated standard errors for the different situations in your example. You'll probably find that the estimated RRR increases but its estimated standard error goes to hell (increases much more). This is a problem with Wald-type tests that has been pointed out before (eg, see Hauck & Donner, JASA 1977, w/ corrrection in 1980). The delta method (especially for anti-log functions of coefficients) seems to exacerbate that.
Thank you, I think you got it. But what is the solution to the problem? Am I stuck with just OR? Is there a way to calculate RRRs with CIs directly from predicted probabilities with CIs instead?

Michael
The trouble is that you are computing a quantity (RRR) that is "non-standard" (ie, non-linear) from the logistic regression model.
Wald-type tests/CIs via the delta method often perform poorly.

If you insist on logistic regression, try bootstrap perhaps? You may not do better, but I doubt you can do worse.

Or, as others have suggested, try another model where your quantity is a "natural" result.

CD





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________________________________________________________________
Constantine Daskalakis, ScD
Assistant Professor,
Biostatistics Section, Thomas Jefferson University,
211 S. 9th St. #602, Philadelphia, PA 19107
Tel: 215-955-5695
Fax: 215-503-3804
Email: c_daskalakis@mail.jci.tju.edu
Webpage: http://www.jefferson.edu/medicine/pharmacology/bio/
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