[R] Comparing model fits for NLME when models are not nested

[Lindsay Banin]

Hi all,

Many thanks for your advice.

Lindsay 


-----Original Message-----
From: Peter Flom [mailto:peterflomconsulting at mindspring.com] 
Sent: 12 June 2009 11:18
To: Lindsay Banin; 'r-help at r-project.org'
Subject: Re: [R] Comparing model fits for NLME when models are not nested

Lindsay Banin <l.banin05 at leeds.ac.uk> wrote
>Hi there,
>
>I am looking to compare nonlinear mixed effects models that have different nonlinear functions (different types of growth curve)embedded. Most of the literature I can find focuses on comparing nested models with likelihood ratios and AIC. Is there a way to compare model fits when models are not nested, i.e. when the nonlinear functions are not the same?
>

What I like to do in these cases (and, in fact, for comparing model fits in general, even if nested) is graph the results of one vs the other, and of each vs. actual values.  If the predicted values from the two models are very similar, then I can choose based on complexity or some other criterion; if they are not similar, then which is closer to the actual values?  Is the difference large? Is it "worth it"?

It's  not a formal test, but I often find it illuminating.

HTH

Peter



Peter L. Flom, PhD
Statistical Consultant
www DOT peterflomconsulting DOT com