[R] Interaction terms in logistic regression using glm

[Greg Snow]

The Predict.Plot and TkPredict functions in the TeachingDemos package can also help with visualizing what the model means and the effect of the different terms.

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111


> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Kjetil Halvorsen
> Sent: Thursday, April 29, 2010 8:46 PM
> To: Andrew Miles
> Cc: r-help at r-project.org
> Subject: Re: [R] 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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> >
> 
> ______________________________________________
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