Date: Wed, 12 Oct 2005 22:09:51 -0700
Reply-To: David L Cassell <davidlcassell@MSN.COM>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: David L Cassell <davidlcassell@MSN.COM>
Subject: Re: Difference in two F tests
Content-Type: text/plain; format=flowed
>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
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
then it makes no sense at all: imagine regressing 4 really highly
regressors for your first case and getting a huge F, then regressing 6
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
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.
David L. Cassell
3115 NW Norwood Pl.
Corvallis OR 97330
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