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Empirical likelihood-based adjustmen...

Luta, Gheorghe.

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Empirical likelihood-based adjustment methods.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Empirical likelihood-based adjustment methods./
Author:	Luta, Gheorghe.
Description:	157 p.
Notes:	Advisers: Pranab Sen; Gary Koch.
Contained By:	Dissertation Abstracts International67-05B.
Subject:	Biology, Biostatistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3219134
ISBN:	9780542715389

Empirical likelihood-based adjustment methods.
Luta, Gheorghe.

Empirical likelihood-based adjustment methods. - 157 p.

Advisers: Pranab Sen; Gary Koch.

Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2006.

Auxiliary information is frequently used in survey sampling at the estimation stage to increase the precision of estimators. The class of calibration estimators introduced by Deville and Sarndal (1992) is obtained by replacing the design weights with the so-called calibration weights, i.e. the closest weights from the design weights (with respect to a given divergence measure) that satisfy the constraints that incorporate the auxiliary information.

ISBN: 9780542715389Subjects--Topical Terms:

1018416
Biology, Biostatistics.

Empirical likelihood-based adjustment methods.
LDR:02734nam 2200313 a 45 001 963873
005 20110831
008 110831s2006 ||||||||||||||||| ||eng d
020 $a 9780542715389
035 $a (UMI)AAI3219134
035 $a AAI3219134
040 $a UMI $c UMI
100 1 $a Luta, Gheorghe. $3 1286936
245 1 0 $a Empirical likelihood-based adjustment methods.
300 $a 157 p.
500 $a Advisers: Pranab Sen; Gary Koch.
500 $a Source: Dissertation Abstracts International, Volume: 67-05, Section: B, page: 2308.
502 $a Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2006.
520 $a Auxiliary information is frequently used in survey sampling at the estimation stage to increase the precision of estimators. The class of calibration estimators introduced by Deville and Sarndal (1992) is obtained by replacing the design weights with the so-called calibration weights, i.e. the closest weights from the design weights (with respect to a given divergence measure) that satisfy the constraints that incorporate the auxiliary information.
520 $a The presence of covariate information in experimental design situations is similar to the presence of auxiliary information in survey sampling. Methods for nonparametric covariance adjustment from Quade (1967), Puri and Sen (1971), Koch et al. (1982), and Koch et al. (1998) are similar to the calibration methods for the two survey samples described by Zieschang (1990). In all these cases the covariance-adjusted estimators are obtained from the unadjusted estimators by minimizing a quadratic criterion subject to equal means constraints on the covariates.
520 $a Ideas from survey sampling are used to generalize previously mentioned methods for nonparametric covariance adjustment. First, an empirical likelihood-based adjustment method is proposed for the construction of confidence intervals for the difference between means. A stratified version of the method and related methods that use criteria based on other divergence measures are described. Next, empirical likelihood-based adjustment methods are developed for the difference between more general parameters of interest under more general constraints. Finally, alternative empirical likelihood-based methods, that use a weighted empirical likelihood criterion, are developed for the construction of confidence intervals for the difference between means and stratified versions.
590 $a School code: 0153.
650 4 $a Biology, Biostatistics. $3 1018416
650 4 $a Statistics. $3 517247
690 $a 0308
690 $a 0463
710 2 $a The University of North Carolina at Chapel Hill. $3 1017449
773 0 $t Dissertation Abstracts International $g 67-05B.
790 $a 0153
790 1 0 $a Koch, Gary, $e advisor
790 1 0 $a Sen, Pranab, $e advisor
791 $a Ph.D.
792 $a 2006
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3219134