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Association analysis of multivariate...

Cheng, Yu.

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Association analysis of multivariate competing risks data.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Association analysis of multivariate competing risks data./
Author:	Cheng, Yu.
Description:	100 p.
Notes:	Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 5167.
Contained By:	Dissertation Abstracts International67-09B.
Subject:	Statistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3234715
ISBN:	9780542880025

Association analysis of multivariate competing risks data.
Cheng, Yu.

Association analysis of multivariate competing risks data. - 100 p.

Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 5167.

Thesis (Ph.D.)--The University of Wisconsin - Madison, 2006.

This thesis focuses on association analyses of multivariate competing risks data. Such data arise in populations based family studies of the genetic epidemiology of chronic diseases where censoring by death may be informative. The work is motivated by the Cache County Study, based in Utah, which investigates associations in dementia onset in aging populations. We first develop nonparametric estimators fro the bivariate cause-specific hazard function and the bivariate cumulative incidence function using bivariate nonexchangeable competing risks data. Summary association measures are proposed and yield formal tests of independence in clusters. The estimators and test statistics are extended to the exchangeable clustered data, where pairwise exchangeability is assumed. We next consider copula models to express both the bivariate cause-specific hazard function and the cumulative incidence function in terms of their marginal. Inferences about the association parameters in the copula models are obtained with some estimating equation techniques. Large-sample properties of the inferential procedures are studied by empirical processes techniques. Large-sample properties of the inferential procedures are studied by empirical processes techniques, their small-sample performances are examined by simulation studies and their practical utilities are illustrated in the analyses of the Cache County study.

ISBN: 9780542880025Subjects--Topical Terms:

517247
Statistics.

Association analysis of multivariate competing risks data.
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245 1 0 $a Association analysis of multivariate competing risks data.
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500 $a Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 5167.
500 $a Adviser: Jason P. Fine.
502 $a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2006.
520 $a This thesis focuses on association analyses of multivariate competing risks data. Such data arise in populations based family studies of the genetic epidemiology of chronic diseases where censoring by death may be informative. The work is motivated by the Cache County Study, based in Utah, which investigates associations in dementia onset in aging populations. We first develop nonparametric estimators fro the bivariate cause-specific hazard function and the bivariate cumulative incidence function using bivariate nonexchangeable competing risks data. Summary association measures are proposed and yield formal tests of independence in clusters. The estimators and test statistics are extended to the exchangeable clustered data, where pairwise exchangeability is assumed. We next consider copula models to express both the bivariate cause-specific hazard function and the cumulative incidence function in terms of their marginal. Inferences about the association parameters in the copula models are obtained with some estimating equation techniques. Large-sample properties of the inferential procedures are studied by empirical processes techniques. Large-sample properties of the inferential procedures are studied by empirical processes techniques, their small-sample performances are examined by simulation studies and their practical utilities are illustrated in the analyses of the Cache County study.
590 $a School code: 0262.
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710 2 0 $a The University of Wisconsin - Madison. $3 626640
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790 1 0 $a Fine, Jason P., $e advisor
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791 $a Ph.D.
792 $a 2006
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3234715