```Date: Wed, 12 Oct 2005 22:09:51 -0700 Reply-To: David L Cassell Sender: "SAS(r) Discussion" From: David L Cassell Subject: Re: Difference in two F tests In-Reply-To: <200510121905.j9CIqw53014566@malibu.cc.uga.edu> Content-Type: text/plain; format=flowed flom@NDRI.ORG wrote: >Suppose you have two linear regressions with the same DV and the same >data. One has 4 IV's, one has 6 IV's. You get an F test for each >model. How is the difference in these F's distributed? > >(as readers will know, I am aware of the problems with various methods >of selecting variables.....but this question came up, and I didn't know >the answer, even in the abstract......I also wasnt sure where to look it >up. This is a trick question. There is no answer. Even assuming that the 4 IVs and nested within the 6 IVs, the difference in the F tests is still meaningless. And, if the sets of regressors are not nested, then it makes no sense at all: imagine regressing 4 really highly significant regressors for your first case and getting a huge F, then regressing 6 versions of white noise for your second case and getting an F near 1. What is even the point of looking at the difference? If the 4 IVs are nested inside the 6 IVs, then you can look at the difference between the sums of squares, and treat that as testable against the SSE. You can get an F test that way. If things are not simple linear regression, then you ought to be looking at the difference between the values of -2logL instead, and getting a chi-squared test. HTH, David -- David L. Cassell mathematical statistician Design Pathways 3115 NW Norwood Pl. Corvallis OR 97330 _________________________________________________________________ Express yourself instantly with MSN Messenger! Download today - it's FREE! http://messenger.msn.click-url.com/go/onm00200471ave/direct/01/ ```

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