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Re: Non-Nested Models-model selection

To: Pravin <jadhavpr@vcu.edu>
Subject: Re: Non-Nested Models-model selection
From: Prof Brian Ripley <ripley@stats.ox.ac.uk>
Date: Thu, 25 Mar 2004 06:11:49 +0000 (GMT)
Cc: s-news@wubios.wustl.edu
In-reply-to: <04C15615C183B043A3D804C5B989844B076D1A40@cdsx08.cder.fda.gov>
Is this a linear model?
Which of your terms are factors?
Is intecept vs intercept a typo?

The models might be nested, depending on the answers. A LRT statistic is 
only even defined for a nested pair of models.

As to your title, the best way I know is to test predictions of the 
models on a test set.  This is not an S question, and I don't know where 
to begin without knowing your background.  I suggest you seek local expert 
statistical advice.

On Wed, 24 Mar 2004, Pravin wrote:

> > Could you please suggest references or relevant links for model selection
> > metric(s) that can be used while dealing with non-nested models:- 
> > 
> > For simplicity, I have two competing models:
> > Model A- Y~intecept+ (alpha+beta*covariate)*time
> > Model B- Y~intercept+beta*covariate+alpha*time
> > In a nutshell, I am testing if covariate is affecting the slope or the
> > intercept. As I understand this, the likelihood ratio statistic will not
> > be asymptotically distributed as a chi-square random variable. So it is
> > not a straightforward comparison using likelihood ratio. Please share some
> > of your experiences and different approaches.

-- 
Brian D. Ripley,                  ripley@stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595


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