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Re: st: Chi-square test for Categorical Data Analysis


From   "Austin Nichols" <austinnichols@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Chi-square test for Categorical Data Analysis
Date   Wed, 19 Sep 2007 14:05:20 -0400

David Radwin <radwin@berkeley.edu>:
Any technique may lead you astray, but the technique you describe is,
I suspect, demonstrably inferior to others.  The reference you cite
applies only to estimating the mean or median of an open-ended
category with a Pareto distribution, and its abstract says that "the
choice of method and the selection of a mean or median estimator for
the open-ended category midpoint have substantial effects on analyses
in which income is the dependent variable."

The -intreg- approach proposed by Maarten relies on some shaky
assumptions, but I expect it is far preferable to imputing the
midpoint of intervals and testing for a difference in means as if you
have real data.

On 9/19/07, David Radwin <radwin@berkeley.edu> wrote:
> It is true, of course, as with many statistical techniques, that this
> technique may lead you astray. I have not done any simulations
> myself, but I will refer you again to the reference in my original
> posting:
>
> Parker, R. N., & Fenwick, R. (1983). The Pareto curve and its utility
> for open-ended income distributions in survey research. Social
> Forces, Vol. 61, No. 3, 872-885.
> http://www.jstor.org/view/00377732/di010900/01p0014t/0
>
> David
>
> At 11:31 AM -0400 9/19/07, Austin Nichols wrote:
> >David Radwin <radwin@berkeley.edu>:
> >
> >I think it's fairly easy to prove via counterexample or simulation
> >that this can easily give the wrong answer.  Can you give a reference
> >that supports it?
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