RE: st: Moderation effect by splitting the sample

["David Radwin" <dradwin@mprinc.com>]

Rebecca,

Sometimes you want to present a result in a simpler or less technical way,
perhaps to a non-expert audience. It is often easier and more parsimonious
to compare two groups, whether verbally or in a table or graph. The cost
is some loss in power. But it may be possible to present the continuous
relationship, too, perhaps in an appendix or some other less prominent
fashion.

For an example of how income (a continuous variable that could be split
into two groups for simplicity) is related to voting in US presidential
elections, please see the work I referred to earlier:

Gelman, A., & Park, D. K. (2009). Splitting a predictor at the upper
quarter or third and the lower quarter or third. The American
Statistician, 63(1), 1-8.
http://www.stat.columbia.edu/~gelman/research/published/thirds5.pdf 

David
--
David Radwin
Senior Research Associate
MPR Associates, Inc.
2150 Shattuck Ave., Suite 800
Berkeley, CA 94704
Phone: 510-849-4942
Fax: 510-849-0794

www.mprinc.com


> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
> statalist@hsphsun2.harvard.edu] On Behalf Of Rebecca Pope
> Sent: Thursday, December 20, 2012 1:24 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: Moderation effect by splitting the sample
> 
> Maarten wrote: "Splitting a sample means that you added an interaction
> term with all variables. This is typically not what you want, and
> often leads to a severe loss of power."
> 
> My understanding is that you would only do this when you have natural
> groups and a strong theoretical reason to not force equality in their
> variances. Is there any other situation where this approach is
> warranted?
> 
> 
> Thanks,
> Rebecca
> 
> 
> 
> 
> On Thu, Dec 20, 2012 at 1:53 PM, Maarten Buis <maartenlbuis@gmail.com>
> wrote:
> > On Thu, Dec 20, 2012 at 8:42 PM, Ebru Ozturk wrote:
> >> For non-linear models, I want to test the moderation effect of X
> variable. Can I test this moderation effect by spliting the sample
> according to X variable (moderator)?
> >
> > That is typically inefficient. Moderation is just an interaction
> > effect. Splitting a sample means that you added an interaction term
> > with all variables. This is typically not what you want, and often
> > leads to a severe loss of power. It is even worse if your variable x
> > is continuous and you are splitting the sample by first making it
> > categorical by splitting it at some arbitrary number (e.g. the median
> > from your previous question). That is a very bad idea, as you would
> > loose even more information that way. Instead you should just add your
> > interaction effect and interpret it correctly. Various examples are
> > given here:
<http://www.maartenbuis.nl/publications/interactions.html>.
> >
> > -- Maarten
> >
> > ---------------------------------
> > Maarten L. Buis
> > WZB
> > Reichpietschufer 50
> > 10785 Berlin
> > Germany
> >
> > http://www.maartenbuis.nl
> > ---------------------------------
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