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

[Michael Morrison <Morrimic@niacc.edu>]

Hi Bill,

I'm not sure I understand the issue. With two binary predictors you have 
4 basic combinations (1-1, 1-0, 0-1 and 0-0), producing 4 different 
logits and 4 different odds; exp(logit). With the 0-0 combination the 
logit is equal to the constant.

Mike




On 9/21/2010 6:24 PM, Dr. Bill Westman wrote:
> 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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> > >
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