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Hypothesis testing in GWAS and stati...

Swanson, David Michael.

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Hypothesis testing in GWAS and statistical issues with compensation in clinical trials.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Hypothesis testing in GWAS and statistical issues with compensation in clinical trials./
Author:	Swanson, David Michael.
Description:	60 p.
Notes:	Source: Dissertation Abstracts International, Volume: 74-10(E), Section: B.
Contained By:	Dissertation Abstracts International74-10B(E).
Subject:	Biology, Biostatistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3567085
ISBN:	9781303187216

Hypothesis testing in GWAS and statistical issues with compensation in clinical trials.
Swanson, David Michael.

Hypothesis testing in GWAS and statistical issues with compensation in clinical trials. - 60 p.

Source: Dissertation Abstracts International, Volume: 74-10(E), Section: B.

Thesis (Ph.D.)--Harvard University, 2013.

We first show theoretically and in simulation how power varies as a function of SNP correlation structure with currently-implemented gene-based testing methods. We propose alternative testing methods whose power does not vary with the correlation structure. We then propose hypothesis tests for detecting prevalence-incidence bias in case-control studies, a bias perhaps overrepresented in GWAS due to currently used study designs. Lastly, we hypothesize how different incentive structures used to keep clinical trial participants in studies may interact with a background of dependent censoring and result in variation in the bias of the Kaplan-Meier survival curve estimator.

ISBN: 9781303187216Subjects--Topical Terms:

1018416
Biology, Biostatistics.

Hypothesis testing in GWAS and statistical issues with compensation in clinical trials.
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020 $a 9781303187216
035 $a (MiAaPQ)AAI3567085
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040 $a MiAaPQ $c MiAaPQ
100 1 $a Swanson, David Michael. $3 2104960
245 1 0 $a Hypothesis testing in GWAS and statistical issues with compensation in clinical trials.
300 $a 60 p.
500 $a Source: Dissertation Abstracts International, Volume: 74-10(E), Section: B.
500 $a Advisers: Rebecca Betensky; Christoph Lange.
502 $a Thesis (Ph.D.)--Harvard University, 2013.
520 $a We first show theoretically and in simulation how power varies as a function of SNP correlation structure with currently-implemented gene-based testing methods. We propose alternative testing methods whose power does not vary with the correlation structure. We then propose hypothesis tests for detecting prevalence-incidence bias in case-control studies, a bias perhaps overrepresented in GWAS due to currently used study designs. Lastly, we hypothesize how different incentive structures used to keep clinical trial participants in studies may interact with a background of dependent censoring and result in variation in the bias of the Kaplan-Meier survival curve estimator.
590 $a School code: 0084.
650 4 $a Biology, Biostatistics. $3 1018416
650 4 $a Health Sciences, Epidemiology. $3 1019544
690 $a 0308
690 $a 0766
710 2 $a Harvard University. $b Biostatistics. $3 2104931
773 0 $t Dissertation Abstracts International $g 74-10B(E).
790 $a 0084
791 $a Ph.D.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3567085