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Semiparametric failure-time regressi...

Hu, Chengcheng.

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Semiparametric failure-time regression with mismeasured or missing covariates.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Semiparametric failure-time regression with mismeasured or missing covariates./
Author:	Hu, Chengcheng.
Description:	142 p.
Notes:	Chair: Danyu Lin.
Contained By:	Dissertation Abstracts International62-08B.
Subject:	Biology, Biostatistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3022851
ISBN:	0493337113

Semiparametric failure-time regression with mismeasured or missing covariates.
Hu, Chengcheng.

Semiparametric failure-time regression with mismeasured or missing covariates. - 142 p.

Chair: Danyu Lin.

Thesis (Ph.D.)--University of Washington, 2001.

This dissertation deals with the estimation of semiparametric regression models, including the Cox proportional hazards model and accelerated failure time model, based on censored data when the covariates are measured with error or missing. For the problem of Cox regression with covariate measurement error, we consider the case when there is a validation set, in which the true covariate is measured precisely, as well as the situation when only replicate surrogate measurements are available. Both univariate and multivariate failure-time data are studied. For the problem of Cox regression with missing covariates, the true covariate is first modeled using regression, then the naive imputation method is corrected to remove bias. The problem of accelerated failure time model with missing covariates is also considered. In all these models, no distributional form is imposed on the covariate or the error. We develop consistent and asymptotically normal estimators for the parameters of interest. The finite-sample properties of the proposed estimators are assessed through extensive simulation studies. Illustrations with real examples are provided.

ISBN: 0493337113Subjects--Topical Terms:

1018416
Biology, Biostatistics.

Semiparametric failure-time regression with mismeasured or missing covariates.
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005 20110427
008 110427s2001 eng d
020 $a 0493337113
035 $a (UnM)AAI3022851
035 $a AAI3022851
040 $a UnM $c UnM
100 1 $a Hu, Chengcheng. $3 1252693
245 1 0 $a Semiparametric failure-time regression with mismeasured or missing covariates.
300 $a 142 p.
500 $a Chair: Danyu Lin.
500 $a Source: Dissertation Abstracts International, Volume: 62-08, Section: B, page: 3445.
502 $a Thesis (Ph.D.)--University of Washington, 2001.
520 $a This dissertation deals with the estimation of semiparametric regression models, including the Cox proportional hazards model and accelerated failure time model, based on censored data when the covariates are measured with error or missing. For the problem of Cox regression with covariate measurement error, we consider the case when there is a validation set, in which the true covariate is measured precisely, as well as the situation when only replicate surrogate measurements are available. Both univariate and multivariate failure-time data are studied. For the problem of Cox regression with missing covariates, the true covariate is first modeled using regression, then the naive imputation method is corrected to remove bias. The problem of accelerated failure time model with missing covariates is also considered. In all these models, no distributional form is imposed on the covariate or the error. We develop consistent and asymptotically normal estimators for the parameters of interest. The finite-sample properties of the proposed estimators are assessed through extensive simulation studies. Illustrations with real examples are provided.
590 $a School code: 0250.
650 4 $a Biology, Biostatistics. $3 1018416
650 4 $a Health Sciences, Public Health. $3 1017659
650 4 $a Statistics. $3 517247
690 $a 0308
690 $a 0463
690 $a 0573
710 2 0 $a University of Washington. $3 545923
773 0 $t Dissertation Abstracts International $g 62-08B.
790 $a 0250
790 1 0 $a Lin, Danyu, $e advisor
791 $a Ph.D.
792 $a 2001
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3022851