Selecting all Treatments Better than a Control using Existing Tables

Roger L. Berger

doi:10.1080/03610928108828170

Selecting all Treatments Better than a Control using Existing Tables

Roger L. Berger

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

In this paper subset selection procedures for selecting all treatment populations with means larger than a control population are proposed. The treatments and control are assumed to have a multivariate normal distribution. Various covariance structures are considered. All of the proposed procedures are easily implemented using existing tables of the multivariate normal and multivariate t distributions. Some other procedures which have been proposed require extensive and unavailable tables for their implementation.

Original language	English (US)
Pages (from-to)	2025-2037
Number of pages	13
Journal	Communications in Statistics - Theory and Methods
Volume	10
Issue number	20
DOIs	https://doi.org/10.1080/03610928108828170
State	Published - Jan 1 1981
Externally published	Yes

Keywords

P*-condition
multivariate normal
multivariate t
repeated measures
subset selection

ASJC Scopus subject areas

Statistics and Probability

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10.1080/03610928108828170

Cite this

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abstract = "In this paper subset selection procedures for selecting all treatment populations with means larger than a control population are proposed. The treatments and control are assumed to have a multivariate normal distribution. Various covariance structures are considered. All of the proposed procedures are easily implemented using existing tables of the multivariate normal and multivariate t distributions. Some other procedures which have been proposed require extensive and unavailable tables for their implementation.",

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author = "Berger, {Roger L.}",

note = "Funding Information: This research was supported in part by U.S. Army Research",

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N2 - In this paper subset selection procedures for selecting all treatment populations with means larger than a control population are proposed. The treatments and control are assumed to have a multivariate normal distribution. Various covariance structures are considered. All of the proposed procedures are easily implemented using existing tables of the multivariate normal and multivariate t distributions. Some other procedures which have been proposed require extensive and unavailable tables for their implementation.

AB - In this paper subset selection procedures for selecting all treatment populations with means larger than a control population are proposed. The treatments and control are assumed to have a multivariate normal distribution. Various covariance structures are considered. All of the proposed procedures are easily implemented using existing tables of the multivariate normal and multivariate t distributions. Some other procedures which have been proposed require extensive and unavailable tables for their implementation.

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KW - multivariate normal

KW - multivariate t

KW - repeated measures

KW - subset selection

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Selecting all Treatments Better than a Control using Existing Tables

Abstract

Keywords

ASJC Scopus subject areas

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