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st: RE: RES: RE: Poisson Regression
From
"Visintainer, Paul" <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
st: RE: RES: RE: Poisson Regression
Date
Mon, 14 Feb 2011 16:01:31 -0500
Jose,
The McNutt articles (in my previous reply) suggest that the conversion method can produce biased point estimates and confidence intervals that are too narrow, particularly in multivariable settings. Note that in his help file on -oddsrisk-, Hilbe uses Poisson regression with the robust standard errors as a comparison for the output of his -oddsrisk- program.
-p
________________________________________________
Paul F. Visintainer, PhD
Baystate Medical Center
Springfield, MA 01199
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of José Maria Pacheco de Souza
Sent: Monday, February 14, 2011 2:15 PM
To: [email protected]
Subject: st: RES: RE: Poisson Regression
Dear Alexandra and Paul:
The user written -oddsrisk- by Joseph M. Hilbe, Arizona State University
---- [email protected]; [email protected] may be a good approach:
"Conversion from Logistic Odds Ratios to Risk Ratios
oddsrisk y(1/0) riskfactor(1/0) varlist [fw=countvariable] <if> <in>
oddsrisk converts logistic regression odds ratios to relative risk ratios by
the formula described below. Source: Zhang and K. Yu, 1998. Frequency
weights
are allowed in order to calculate odds and risk ratios from 2 x 2 tables.
The
response must be binary, as does the first predictor, which is considered to
be
the risk factor or exposure..."
José Maria Pacheco de Souza
Professor Titular, aposentado; Colaborador Sênior
Departamento de Epidemiologia/Faculdade de Saúde Pública/Universidade de São
Paulo
Av. Dr. Arnaldo, 715 - São Paulo, Capital - cep 01246-904
Fones: FSP= (11)3061-7747 Res= (11)3714-2403; (11)3768-8612
www.fsp.usp.br/~jmpsouza
<snip>
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