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)? If not, is there a function somewhere
that allows for correct estimation?
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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