Re: [R] Logistic Stepwise Criterion

From: <Bill.Venables_at_csiro.au>
Date: Wed, 02 Mar 2011 09:39:50 +1100

The "probability OF the residual deviance" is zero. The significance level for the residual deviance according to its asymptotic Chi-squared distribution is a possible criterion, but a silly one. If you want to minimise that, just fit no variables at all. That's the best you can do. If you want to maximise it, just minimise the deviance itself, which means include all possible variables in the regression, together with as many interactions as you can as well. (Incidently R doesn't have restrictions on how many interaction terms it can handle, those are imposed my your computer.)

I suggest you think again about what criterion you really want to use. Somehow you need to balance fit in the training sample against some complexity measure. AIC and BIC are commonly used criteria, but not the only ones. I suggest you start with these and see if either does the kind of job you want.

Stepwise regression with interaction terms can be a bit tricky if you want to impose the marginality constraints, but that is a bigger issue.

Bill Venables.

-----Original Message-----
From: r-help-bounces_at_r-project.org [mailto:r-help-bounces_at_r-project.org] On Behalf Of Mano Gabor Toth Sent: Wednesday, 2 March 2011 6:44 AM
To: r-help_at_r-project.org
Subject: [R] Logistic Stepwise Criterion

Dear R-help members,

I'd like to run a binomial logistic stepwise regression with ten explanatory variables and as many interaction terms as R can handle. I'll come up with the right R command sooner or later, but my real question is whether and how the criterion for the evaluation of the different models can be set to be the probability of the residual deviance in the Chi-Square distribution (which would be more informative of overall model fit than AIC).

Thanks in advance for all your help.

Kind regards,

Mano Gabor TOTH
MA Political Science
Central European University

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