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Re: st: logistic regression with orthogonal predictors


From   Richard Williams <Richard.A.Williams.5@ND.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: logistic regression with orthogonal predictors
Date   Mon, 15 May 2006 15:49:11 -0500

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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