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Re: st: Re: Measures of fit in clogit

From   "Clive Nicholas" <>
Subject   Re: st: Re: Measures of fit in clogit
Date   Wed, 2 Feb 2005 02:32:53 -0000 (GMT)

Naoko Taniguchi replied:

> The count R square seems good because it is said that it can describe
> 'the proportion of correct prediction (i.e. the correct predicted vote
> / the observed vote).  But this measure seem contradict to others.
> Model A


> Count R2:                      0.538
> Model B


> Count R2:                      0.557

If you've read pages 93 and 94 of Long and Freese (2001) - which gives the
formula for count R^2, you'll know why. Precisely because " is
possible to correctly predict at least 50 percent of the cases by choosing
the outcome category with the largest percentage of cases" is certainly
the main reason that I wouldn't trust this statistic as far as I could
throw it.*

Via -fitstat-, Long and Freese do calculate the adjusted count R^2, so
called because it adjusts for the largest row marginal (formula given on
page 94). However, in all of the fixed-effect logit models I've fitted to
my own electoral data (as well as to play data such as from -webuse
union-), -fitstat- never once offers the adjusted count R^2 statistic
(even when including just one (dummy) independent variable), presumably
because it cannot be calculated after -clogit-. I'd be interested to find
out from others if they have successful experiences of this.

I repeat my advice from earlier: if you value what the R^2 of your model
is telling you, put most of your cash on reporting the adjusted McFadden's

CLIVE NICHOLAS        |t: 0(044)7903 397793
Politics              |e:
Newcastle University  |


Long JS and Freese S (2nd ed., 2001) REGRESSION MODELS FOR CATEGORICAL

*Personal best: 11 feet, 2 inches at the All-England Count R^2-Throwing
Championships at Sunningdale last August.

*   For searches and help try:

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