Interaction terms in logistic regression using glm
see comments below.
On Wed, Apr 28, 2010 at 4:29 PM, Andrew Miles <rstuff.miles at gmail.com> wrote:
I recently became aware of the article by Ai and Norton (2003) about how interaction terms are problematic in nonlinear regression (such as logistic regression). ?They offer a correct way of estimating interaction effects and their standard errors. My question is: ?Does the glm() function take these corrections into account when estimating interaction terms for a logistic regression (i.e. when family=binomial)?
No. ?If not, is there a function somewhere that allows for
correct estimation?
The estimation you get from glm is correct. The discussion in the paper you referred is about how to interpret the estimation results! A google search on the referred paper (you did'nt give the title), show up various later papers referring to it, and not supporting their conclusions. Linear (and non-linear) model books badly needs chapters with titles such as "post-estimation analysis". glm does the estimation for you. It cannot do the analysis for you! Probably you are looking for something such as CRAN package "effects". Kjetil
I've looked the documentation for glm and couldn't find an answer, nor have I seen the issue addressed in the forums or in the examples of logistic regression in R that I've found online. Thanks! Andrew Miles
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