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Re: st: RE: ODDSRISK module to convert Logistic Odds Ratios to Risk Ratios

From   Ricardo Ovaldia <[email protected]>
To   [email protected]
Subject   Re: st: RE: ODDSRISK module to convert Logistic Odds Ratios to Risk Ratios
Date   Thu, 20 Dec 2007 10:51:22 -0800 (PST)

Thank you Dr. Hilbe. However, I think that this method
is only applicable to cohort studies and not to
case-control studies. Is that correct?

Thank you,

--- [email protected] wrote:

> 'ODDSRISK': module to  convert Logistic Odds Ratios
> to Risk Ratios now on SSC
> I thought I had  posted a notice about this module
> to the list yesterday, but 
> it seems that it  did 
> not make it. I take the Digest, so do not see what
> is posted until the  next 
> day. I apologize if the earlier one is posted today,
> as well as this one.  
> Zhang and Yu (1998, JAMA) proposed an algorithm to
> convert binary  logistic 
> regression odds ratios to estimated risk ratios. I
> have seen the method  used 
> in a number of medical research articles, and had
> written about the method  in 
> a book I am writing. I noticed a couple of Statalist
> communications during  
> the past couple of weeks related to the relationship
> of odds ratio to risk  
> ratio. I wrote about this relationship in my
> "Negative Binomial Regression", but  
> not about this method and its rationale. Anyhow, I
> thought it might be helpful 
>  to those interested in using this method to release
> a Stata implementation 
> now  rather than with the forthcoming book several
> months from now. I wrote the 
>  program in such a manner that the logistic odds
> ratio, estimated risk ratio, 
> and  95% confidence intervals of the estimated risk
> ratios are displayed for 
> each  predictor in the model. The incidence rate of
> the unexposed risk factor, 
> or  primary predictor of interest (binary (1/0)),
> which is required for 
> calculation,  is also displayed. 
> The estimated risk ratios are particularly important
>  when we wish to use 
> terms such as "likely" in place of "odds of" when 
> interpreting the odds ratio of 
> a logistic model. This is primarily the case with 
> the odds ratio is under 
> 0.5 or over 2.5 and the incidence rate is greater
> than  10%. To say something 
> like, "patients having an anterior infarct are 50%
> more  likely to die within 48 
> hours of hospital admission than are patients having
>  just sustained an 
> infarct at another primary site", is using risk
> language. Such  language may be 
> justified for many logistic models, but not all. 
> Using the  estimated risk 
> values and CI's calculated by -oddsrisk- presumably
> enhance the  justification for 
> using risk language with logistic models when the
> conditions  specified above 
> obtain. 
> Kit Baum has graciously posted the program,  called
> -oddsrisk- and the 
> associated help file to the SSC site.  You can 
> download it by typing 
> . ssc install oddsrisk
> on the Stata  command line. 
> I have pasted the SSC site module description under
> my  name below. 
> Best,  Joseph  Hilbe
> oddsrisk converts logistic regression odds  ratios
> to relative
> risk ratios. When the  incidence of an outcome is
> common in the
> study  population; i.e. greater than 10%, the
> logistic  regression
> odds ratio no longer approximates  the risk ratio.
> As the
> incidence rate becomes  more frequent, the more the
> odds ratio
> overestimates the risk  ratio when its value is
> greater than  1,
> and the more it underestimates the risk  ratio  when
> under one. J.
> Zhang and K. Yu  proposed a method of adjusting the
> logistic
> regression odds ratio in a cohort study or clinical
> trial so  that
> it approximates  the risk ratio.  This is
> particularly important
> when the odds  ratio is greater than  2.5 or under
> 0.5. The  method
> has also been shown to be applicable  for
> retrospective  and
> observational  studies as well.
> Author: Joseph M.  Hilbe
> Arizona State  University
> [email protected]   or   [email protected]
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Ricardo Ovaldia, MS
Oklahoma City, OK

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