R help - Apr 2010 - Interaction terms in logistic regression using glm

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

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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