On Wed, 8 Oct 2003 10:33:49 +0200, "Lughnasad" <[EMAIL PROTECTED]> wrote:
> > "albinali" <[EMAIL PROTECTED]> escribi� en el mensaje > news:[EMAIL PROTECTED] > > Hi, > > With non-ordinal categorical data, I was told that logistic regression > is > > likely to do a better job, why is that, whats the problem with linear > > regression? > > In the case of what the dependient variable be dichotomous, if you do a > multiple regression you are violating the assumptions required for > inference. In particular the regression errors are not normally distribuited > neither their variance is constant. Comment on the comment - Since the multiple regression on a dichotomy is mathematically identical to the problem of Fisher's discriminant function, the multiple regression is pretty robust for the job. You can do t-tests on dichotomous variables and the tests will be pretty accurate, too, and those are the same shape of residuals. > If you do a multiple regression the final conclusions can be misleading. > -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html "Taxes are the price we pay for civilization." . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
