I am using it to test the moderating effect of motivations of media use
on the impact of media use on a dependent variable. So, no, I don't
think I am testing for group differences (like the Chow test in linear
models would). In fact, while I used a dummy variable in my example, I
am interacting two continuous variables, but I wanted to keep the
example simple.
(but thanks for the link anyway, I am interested in that for different
reasons)
Daniel
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of
> Hoetker, Glenn
> Sent: Saturday, March 19, 2005 10:13 AM
> To: [email protected]
> Subject: RE: st: Interaction terms in a logit model
>
>
> If your dummy variable does in fact reflect that you are
> looking at differences across groups, you really need to read
> Allison's 1999 piece cited below. Partially building on
> Allison's piece, I have a paper in which I test whether
> cross-group differences in residual variation really matter
> (as opposed to being a theoretical concern without practical
> impact). Monte Carlo simulations indicate that even small
> differences in residual variation can indeed invalidate
> cross-group comparisons. Using interaction terms to model
> different groups in logit models ends up being particularly
> risky--you can even end up with significant results in the
> opposite direction! Allison's tests, while they have some
> limitations, are a definite improvement on common practice.
>
> If you are interested, the paper is at
> http://www.business.uiuc.edu/ghoetker/documents/Hoetker_comp_l
> ogit.pdf.
> You can install the Stata code it discusses from within Stata:
>
> net from http://www.business.uiuc.edu/ghoetker
>
> and carry on as normal from there. Please be aware that the
> software is work in progress. In particular, there is
> absolutely no sanity checking.
>
> As far as I know, so long as you aren't using the interaction
> term to model cross-group differences (which is what
> introduces the potential for differences in residual
> variation), you should be okay.
>
> Glenn
>
> Glenn Hoetker
> Assistant Profess of Strategy
> College of Business
> University of Illinois at Urbana-Champaign
> [email protected]
>
>
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of
> Richard Williams
> Sent: Saturday, March 19, 2005 11:51 AM
> To: [email protected]
> Subject: Re: st: Interaction terms in a logit model
>
> At 10:00 PM 3/18/2005 -0800, Daniel Schneider wrote:
> >Dear List,
> >
> >I have read the articles by Norton, Wang, Ai (2004) as well as their
> >more theoretical paper (Ai & Norton (2000)) and I am aware of other
> >literature describing the same problem. I think I understood the
> >theoretical problems and reasoning behind their approach, but
> >unfortunately I really have a hard time of really
> understanding what I
> >have to do when I use interaction terms in a logit regression.
>
> Daniel, could you provide more precise citations for the
> articles you are
> mentioning? I'd be curious to read more about what they say.
>
> Not having read these papers, I don't know specifically what
> your concern
> is, but Paul Allison's "Comparing Logit and Probit
> Coefficients Across
> Groups," SOCIOLOGICAL METHODS & RESEARCH, Vol. 28 No. 2,
> November 1999
> 186-208, may be worth a look. Here is the abstract:
>
> "In logit and probit regression analysis, a common practice
> is to estimate
> separate models for two or more groups and then compare
> coefficients across
> groups. An equivalent method is to test for interactions
> between particular
> predictors and dummy (indicator) variables representing the
> groups. Both
>
> methods may lead to invalid conclusions if residual variation differs
> across groups. New tests are proposed that adjust for unequal
> residual
> variation."
>
>
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
> FAX: (574)288-4373
> HOME: (574)289-5227
> EMAIL: [email protected]
> WWW (personal): http://www.nd.edu/~rwilliam
> WWW (department): http://www.nd.edu/~soc
>
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