Dunnett's many-to-one test and least square means.

Abstract:

:Dunnett's many-to-one test is used frequently today, especially in dose-finding studies. Using Dunnett's test, the Type I error level for the comparison between the raw mean of the control and the raw means of the study drug groups can be exactly calculated for the normal data. However, this computability depends on the independence of the raw means. Unfortunately, this independence does not exist for the model-based likelihood estimates (least square means) in the cases of ANCOVA and two-way ANOVA models without interaction for unbalanced data. This paper investigates this dependence between the least square means and derives some new procedures to calculate the joint distribution of the statistic for Dunnett's test.

journal_name

J Biopharm Stat

authors

Shun Z,Silverberg A,Chang CK,Ouyang P

doi

10.1081/BIP-120017723

keywords:

subject

Has Abstract

pub_date

2003-02-01 00:00:00

pages

17-28

issue

1

eissn

1054-3406

issn

1520-5711

journal_volume

13

pub_type

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