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Re: st: Logistic regression interpretation - continued questions with ONY binary predictors


From   "Dr. Bill Westman" <webicky@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Logistic regression interpretation - continued questions with ONY binary predictors
Date   Tue, 21 Sep 2010 16:24:12 -0700

Mike.  Thanks.  It seems that this book and others move to models that
are seem to be unrelated to a binary outcome and two binary predictors
(specifically).  With a second binary predictor, many of the
techniques suggested by Long & Freese seem irrelevant.  There isn't
really a "mean" risk - it is either High or NOT.   The fact that I do
not have any continuous predictors makes this case easier -- I think,
but still perplexing to me.  If any listers have insight, please let
me know



On Tue, Sep 21, 2010 at 3:04 PM, Michael Morrison <Morrimic@niacc.edu> wrote:
> I recommend you read Long & Freese (2006) /Regression Models for Categorical
> Dependent Variables Using Stata. It provides interpretation of odds,
> _controlling for covariates_ and ways to test your model's goodness of fit.
> Also of interest is their Spost commands.
>
> Mike
>
> /
>
> On 9/21/2010 4:36 PM, Dr. Bill Westman wrote:
>>
>> Dear Listers: I have more of a stats question than a stata question,
>> but here goes:
>>
>> A simple logistic regression was run - outcome - Survived/Non Survived
>> (1/0), with Group(Treatmeant/Control -- 1/0)&  Risk(High/Low -- 1/0)
>>
>> The results
>>
>> ------------------------------------------------------------------------------
>>        Survived | Odds Ratio   Std. Err.      z    P>|z|     [95%
>> Conf. Interval]
>>
>> -------------+----------------------------------------------------------------
>>     Risk |   4.790295   2.589136     2.90   0.004     1.660699    13.81763
>>    group |   2.111181   .9107981     1.73   0.083     .9063649    4.917538
>>
>> ------------------------------------------------------------------------------
>>
>> Assuming the .10 level of significance was acceptable (for discussion
>> purposes)
>>
>> Can I assume that odds of treatment survival were 2.1  times higher in
>> the treatment Group for LOW risk patients?
>> And for High Risk patients in the treatment group is the adds 4. 8 +
>> 2.1 (or 6 times higher)?
>>
>> Other than test for interactions, can I run a graphs of these two groups?
>>
>> Can I estimate the "average" effect of Treatment across both high and
>> low risk patients?  If so, how?
>>
>> What other tests might I wish to do in Stata?
>>
>> Thanks
>>
>> Bill
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