Re: st: logistic regression with orthogonal predictors

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

At 02:35 PM 5/15/2006, frone@ria.buffalo.edu wrote:
> A colleague asked me about some results with logistic regression.  He had
> two predictors of a binary outcome, call them A and B.  When used alone,
> predictor A was significantly related to the outcome and predictor B was
> not.  Moreover, the correlation between A and B was zero.  When the
> outcome was regressed on the two predictors simultaneously using logistic
> regression both were significantly related to the outcome.  In effect, the
> coefficient for predictor B became larger.  However, when OLS regression
> was used instead, the coefficients for each predictor were the same as
> when entered alone, which is what one would expect.
I discuss this in these two handouts:

http://www.nd.edu/~rwilliam/xsoc694/x04a.pdf

http://www.nd.edu/~rwilliam/xsoc694/x04.pdf

In OLS regression, it is common to estimate a series of models, 
adding additional variables as you go along, and commenting on how 
the effects of early vars change as new vars are added to the 
model.  As these handouts show, that is a potentially dangerous 
practice in logistic regression.


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Richard Williams, Notre Dame Dept of Sociology
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