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RE: st: Classification table from mlogit
From
"Barth Riley" <[email protected]>
To
<[email protected]>
Subject
RE: st: Classification table from mlogit
Date
Mon, 22 Mar 2010 10:20:13 -0500
Thanks, that helps!
Barth
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Maarten buis
Sent: Monday, March 22, 2010 9:31 AM
To: [email protected]
Subject: Re: st: Classification table from mlogit
--- On Mon, 22/3/10, Barth Riley wrote:
> Is there something analogous to lstat, which is used for
> producing a classification table after calling the
> logistic procedure, for mlogit?
It is possible to something similar for -mlogit- by
assigning someone to a category for which (s)he has the
highest predicted probability, rather than assigning a
person to a category for which her/his predicted probability
exceeds 50%.
*---------------------- begin example ------------------------
sysuse auto, clear
recode rep78 1/2=3
mlogit rep78 foreign mpg price
predict pr*
tokenize `e(eqnames)'
gen yhat = cond(pr1 == max(pr1,pr2,pr3), `1', ///
cond(pr2 == max(pr1,pr2,pr3), `2', `3')) if e(sample)
tab rep78 yhat
*------------------------ end example ------------------------
However, I would be very careful when using such a method.
These tables are notoriously sensitive to the marginal
distribution of your dependent variable. If one category is
very common, than you can obtain quite a good looking score
by assigning everybody to that category. Any additional
information from explanatory variables will only marginaly
improve your "fit". Explanatory variables will have a much
biger "impact" on getting the prediction righ when the
marginal proportions of belonging to a category are
approximately equal. It is however doubtful if such a
difference is substantively meaningful, as this difference
comes only from how much variation a baseline model has
left unexplained. So, this sensitivity to the marginal
distribution of your depedent variable is most of the time
not a desirable characteristic for a fit-statistic.
Hope this helps,
Maarten
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.maartenbuis.nl
--------------------------
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