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st: RE: generalized Dunnett's test?


From   "Feiveson, Alan H. (JSC-SK311)" <alan.h.feiveson@nasa.gov>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: generalized Dunnett's test?
Date   Tue, 18 Jan 2011 10:04:48 -0600

It would involve some programming work, but you could try resampling methods, as described in Westfall and Young (Resampling-based Multiple Testing). 


Al

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Airey, David C
Sent: Tuesday, January 18, 2011 8:17 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: generalized Dunnett's test?

.

Dunnett's test is an ANOVA post-hoc test, a many-to-one pairwise test, typically used for comparing many experimental treatments each to a single control following a oneway ANOVA. Is there a generalization of this test for likelihood ratio tests? I have a full model and a set of reduced models (NOT from oneway ANOVAs), where each reduced model constrains the parameters of the control and one treatment group to be shared/equal. Each LRT for the full and a reduced model tests a control vs treatment difference. I can apply a multiple test adjustment to the vector of LRT p-values, like Holm's adjustment, but I'm curious if there is a Dunnett analogue for this situation. Some multiple test procedures assume independence of the tests, but there is the same control group in each pairwise test in Dunnett's situation, and in my set of LRTs. Although I've not simulated it, I'm assuming with many tests, Dunnett's procedure will beat Holm's correction for a many-to-one set of pairwise c!
 omparisons.
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