Re: st: Logistic Regression_Unequal Ns (outcomes)

[Richard Williams <Richard.A.Williams.5@ND.edu>]

At 08:34 AM 3/8/2009, Chao Yawo wrote:
> Hello, I'm preparing to run a logit model predicting the odds of NOT
> testing for an STD.  As you can see from the table below, 4688 (about
> 98%) of respondents have my outcome of interest (i.e., have not tested
> for an STD).  I realized that because of this unequal groupings, all
> crosstabulations have higher proportions within the untested category.
>  I have a feeling that these could bias my estimates in a way. For
> example, given the unequal groupings, I think I am only restricted to
> modeling failure to test (the zero outcome), as modeling for ever
> tested (1) could lead to unstable estimates.  So my question is  what
> possible impact will this have on my model, and what can I do about
> it?  Thanks - Chao
Like Martin says, it doesn't matter which is one and which is 
zero.  Also, my experience is that the classification table, which I 
never use all that much anyway,  is especially worthless when you 
have such an extreme split.
You may wish to check into Gary King's -relogit-.  See

http://gking.harvard.edu/stats.shtml


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Richard Williams, Notre Dame Dept of Sociology
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EMAIL:  Richard.A.Williams.5@ND.Edu
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