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Global Tests for Multiple Outcomes i...

Hebert, Donald Joseph.

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Global Tests for Multiple Outcomes in Randomized Trials.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Global Tests for Multiple Outcomes in Randomized Trials./
作者:	Hebert, Donald Joseph.
面頁冊數:	163 p.
附註:	Source: Dissertation Abstracts International, Volume: 78-05(E), Section: B.
Contained By:	Dissertation Abstracts International78-05B(E).
標題:	Statistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10179054
ISBN:	9781369291698

Global Tests for Multiple Outcomes in Randomized Trials.
Hebert, Donald Joseph.

Global Tests for Multiple Outcomes in Randomized Trials. - 163 p.

Source: Dissertation Abstracts International, Volume: 78-05(E), Section: B.

Thesis (Ph.D.)--University of Rochester, 2016.

Methods for analyses of multiple outcome variables in randomized trials are prevalent throughout the statistical literature. Research for the case where the interest is in evaluating an overall treatment effect across the multiple outcomes has received a great deal of attention due to its importance in practice. This thesis provides a thorough review of current approaches for the analyses of multiple outcomes and suggests a need for an approach that maintains high statistical power under several different alternatives of clinical interest. The proposed methods aim to satisfy this need in the cases of both multivariate normal and mixed outcomes.

ISBN: 9781369291698Subjects--Topical Terms:

517247
Statistics.

Global Tests for Multiple Outcomes in Randomized Trials.
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500 $a Adviser: Michael P. McDermott.
502 $a Thesis (Ph.D.)--University of Rochester, 2016.
520 $a Methods for analyses of multiple outcome variables in randomized trials are prevalent throughout the statistical literature. Research for the case where the interest is in evaluating an overall treatment effect across the multiple outcomes has received a great deal of attention due to its importance in practice. This thesis provides a thorough review of current approaches for the analyses of multiple outcomes and suggests a need for an approach that maintains high statistical power under several different alternatives of clinical interest. The proposed methods aim to satisfy this need in the cases of both multivariate normal and mixed outcomes.
520 $a Multiple clinical outcomes are often measured repeatedly over time and the problem of missing data is ubiquitous in clinical trials. Available methods to account for missing data are discussed in relation to the three sources of correlation stemming from these outcomes in this multivariate longitudinal context. This thesis suggests a novel approach to properly account for missing data when implementing the proposed methods for analyses of the multiple clinical outcomes.
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