RE: st: RE: Poisson Regression

["Visintainer, Paul" <Paul.Visintainer@baystatehealth.org>]

The approaches can be used for prevalence studies.  You have to interpret the output as prevalence ratios, not relative risks.

I also have to promote Brendan's suggestion about using -margins-.  When I have used the approach for cross sectional studies, I got the adjusted prevalences using -margins-.  Reporting the adjusted prevalences make it much easier for a clinical audience to interpret and understand.  I would certainly encourage their use.

-p

________________________________________________
Paul F. Visintainer, PhD
Baystate Medical Center
Springfield, MA 01199


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Alexandra Boing
Sent: Tuesday, February 15, 2011 5:20 AM
To: statalist@hsphsun2.harvard.edu
Subject: RE: st: RE: Poisson Regression

Thanks for considerations! I did mencion that is cross sectional study. Tha'ts no problem, right?
Greetings, Alexandra 

--- Em ter, 15/2/11, Maarten buis <maartenbuis@yahoo.co.uk> escreveu:

> De: Maarten buis <maartenbuis@yahoo.co.uk>
> Assunto: RE: st: RE: Poisson Regression
> Para: statalist@hsphsun2.harvard.edu
> Data: Terça-feira, 15 de Fevereiro de 2011, 8:26
> --- Visintainer, Paul wrote:
> > My frustration is that when the outcome is common and
> > logistic regression is used, there virtually no
> discussion
> > of clinical relevance -- only statistical
> significance,
> > (e.g., is a significant odds ratio of 2.5 clinically
> > relevant?  Perhaps if the base risk is 2%; perhaps
> not
> > if the base risk 73%. 
> 
> This is where Stata has a problem: it automatically
> suppresses
> the display of the baseline odds when you ask for odds
> ratios
> (and baseline hazard when you ask for hazard ratios, and
> baseline incidence rate when you ask for incidence rate
> ratios,
> etc.).
> 
> To me the baseline odds serve two purposes:
> 
> First, is it really helps in communicating the results. By
> 
> discussing it first in the results section of a paper you 
> refresh the readers memory on what an odds is. It also
> makes 
> the model less "magical" if you frame it in number of high
> 
> status jobs, deaths, or successes per low status job,
> survivals, 
> or failures. You frame the model in terms that the reader
> care 
> about.
> 
> Second, it helps when trying to determine the size of of an
> 
> effect. An odds ratio of 2 is not very impressive if the
> baseline
> odds is small 2 times a small number is still a small
> number, 
> while is much more impressive if the baseline odds is
> large.
> Alternatively, if your baseline odds is already 50
> successes per
> failure, then any increase is not going to have much
> substantive
> meaning.
> 
> There is a trick you can use to display the baseline odds,
> which 
> is discussed in a slighly different context in: 
> 
> Roger Newson (2003) "Stata tip 1: The eform() option of
> regress"
> The stata Journal, 3(4), 445.
> <http://www.stata-journal.com/article.html?article=st0054>
> 
> 
> -- Maarten
> 
> Ps. those who have followed the list a while will have
> noticed that
> I made this point before. I hope I did not bore them too
> much.
> 
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
> 
> http://www.maartenbuis.nl
> --------------------------
> 
> 
> 
>       
> 
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> 



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