Thanks Rich, can you suggest a book where I can read about the basis underlying the LR test? The books that I have just tell me where and how to use it, without giving a sufficient theoretic description of why.
Cheers, Brian Rich Ulrich <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>... > On 19 Jan 2002 10:25:10 -0800, [EMAIL PROTECTED] (Brian Leung) > wrote: > > > Greetings, > > > > I've read that the likelihood ratio test is not valid for non-nested > > models. Is this still true if the PF (i.e., multinomial) is the same, > > but the link function differs. > > > > Yes, it is still true. It is the subtraction that allows the > estimates to be *independent* so that the result may be > readily interpreted. > > However, it is also true that people decide and publish using > related criteria for non-nested models. Such conclusions > are not as rigorous, but seem to work in various applications. > Your comparison of link functions sounds familiar, for instance. > > Here is one link I found by searching on > < BIC "information criterion" > , > http://www.saam.com/faq/saam2/right.html > (I keep forgetting how to spell AKAIKE.) ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =================================================================
