This debate has been very interesting and dear to my heart. I have
found it very useful and have obtained some useful references.
However, one of the worrying things for me as a Stata user is that
ALL the GLM models that have failed for me in Stata have worked
OK in SAS.
Patrick
From: Ron�n Conroy <[email protected]>
To: "statalist hsphsun2.harvard.edu" <[email protected]>
Date sent: Thu, 15 Apr 2004 11:39:18 +0100
Subject: Re: st: -binreg- (was: ORs for non-rare outcomes)
Send reply to: [email protected]
> on 14/04/2004 12:01, roger webb at [email protected] wrote:
>
> > I've found that the problems encountered in trying to fit
> > log-binomial models (using either 'binreg' or 'glm link(log)
> > family(binomial)') can be overcome by using the 'modified' Poisson
> > regression approach proposed by Zou (Am J Epidemiol 2004; 159:
> > 702-706).
>
> And see also
>
>
> Alternatives for logistic regression in cross-sectional studies: an
> empirical comparison of models that directly estimate the prevalence
> ratio
>
> http://www.biomedcentral.com/1471-2288/3/21
>
> The paper from Barros and Hirakata, which includes the Stata code for
> each of the models, is free (another cheer for open-access publishing)
> as against the 35 bucks that the Am J Epidemiol want in order for us
> to access research that the taxpayer has already paid for once...
>
> Ronan M Conroy ([email protected])
> Lecturer in Biostatistics
> Royal College of Surgeons
> Dublin 2, Ireland
> +353 1 402 2431 (fax 2764)
>
> --------------------
> Just say no to drug reps
> http://www.nofreelunch.org/
>
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