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Re: st: Logistic regression interpretation -- vs. M-H


From   "Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Logistic regression interpretation -- vs. M-H
Date   Thu, 23 Sep 2010 09:45:38 -0700

If I recall correctly logistic regression is equivalent to MH possibly with small correction to the variance. 

Sent from my iPhone

On Sep 23, 2010, at 9:12 AM, "Dr. Bill Westman" <webicky@gmail.com> wrote:

> helpful and generous with your time.  To other listers who replied --
> thank you as well for your excellent guidance
> 
> I am wondering whether Mantel-Haenszel. is more or less appropriate in
> 2x2x2 situation with binary variables which spans across groups than
> logistic regression.  I am reading Agresti's work which discusses this
> now.  I believe epitab M-H is producing this test (at least I think it
> is).  The results are quite different in terms of statistical
> significance.  I am not sure if you or others have an opinion of the
> differences in these models.
> 
> I hope this last question isn't a nuisance, but there are several
> Stata list posts on this issue and I was not able to come away with a
> meaningful concluston
> 
> Thanks for reading...
> 
> Bill
> 
> On Thu, Sep 23, 2010 at 2:50 AM, Maarten buis <maartenbuis@yahoo.co.uk> wrote:
>> --- On Wed, 22/9/10, Dr. Bill Westman wrote:
>>> Also - those two di statements at show the exact same odds
>>> - was this intentional?
>> 
>> It is important to make a distinction between odds and odds-ratios.
>> The former is a measure of the likelihood of an event, the latter
>> is a measure of how this likelihood differs across groups.
>> 
>> So in the example below we first compute the odds of union membership
>> separately for married and non-married people. Remember that the odds
>> is the expected number of union members per non-union member, so if
>> we observe 10 union members and 20 non-union members then we expect
>> to see 10/20=.5 union member for every non-union member.
>> 
>> After that we look at how the odds of union membership differs between
>> married and non-married women, by computing the ratio.
>> 
>> After that I show that that is exactly what -logit- does.
>> 
>> *--------------------------- begin example --------------------------
>> sysuse nlsw88, clear
>> tab married union
>> di "the odds of union membership for married women is: " 280/942
>> // so there are .30 union members for every non-union member when
>> // the women is married
>> 
>> di "the odds of union membership for non-married women is: " 181/475
>> // so there are .38 union members of every non-union member when the
>> // women is not married
>> 
>> di "the odds of union membership for married women is " ///
>>   (280/942)/(181/475)  " times the odds of union membership" ///
>>   " for non-married women"
>> // so mariage reduces the odds of memebership with 22%
>> 
>> // this odds ratio can be recovered with -logit-.
>> logit union married, or
>> 
>> // the odds can be recovered using -margins.
>> margins , exp(exp(xb())) over(married)
>> *---------------------- end example ---------------------------------
>> 
>> Hope this helps,
>> Maarten
>> 
>> --------------------------
>> Maarten L. Buis
>> Institut fuer Soziologie
>> Universitaet Tuebingen
>> Wilhelmstrasse 36
>> 72074 Tuebingen
>> Germany
>> 
>> http://www.maartenbuis.nl
>> --------------------------
>> 
>> 
>> 
>> 
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