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Re: st: Non-nested models and LRTEST
At 05:52 AM 8/25/2006, Marcello Pagano wrote:
If the models aren't nested you shouldn't do a chi-square contrast
between them. Consider using a BIC test instead, which you can get
by adding the stats option, e.g.
Rho YH wrote:
>If I make a logistic model 1) A = B C D E F G and another model
>2) A = B C D E F H I , which are not necessarily nested each other
>(but one has more variables than the other), are the results of
>LRTEST still relevant ?
>For example, if LRTEST 1) 2) is significant (p<0.05), then is model
>2) better explaining than model 1)?
>Do my ideas make sense?
lrtest m1 m2, stats
There is a brief discussion of BIC and AIC measures on pp. 4-6 of
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
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