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Three Contributions to Latent Variab...

Liu, Xiang.

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Three Contributions to Latent Variable Modeling.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Three Contributions to Latent Variable Modeling./
Author:	Liu, Xiang.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	117 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-06, Section: B.
Contained By:	Dissertations Abstracts International80-06B.
Subject:	Educational tests & measurements. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13420118
ISBN:	9780438713000

Three Contributions to Latent Variable Modeling.
Liu, Xiang.

Three Contributions to Latent Variable Modeling. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 117 p.

Source: Dissertations Abstracts International, Volume: 80-06, Section: B.

Thesis (Ph.D.)--Columbia University, 2019.

This item must not be sold to any third party vendors.

The dissertation includes three papers that address some theoretical and technical issues of latent variable models. The first paper extends the uniformly most powerful test approach for testing person parameter in IRT to the two-parameter logistic models. In addition, an efficient branch-and-bound algorithm for computing the exact p-value is proposed. The second paper proposes a reparameterization of the log-linear CDM model. A Gibbs sampler is developed for posterior computation. The third paper proposes an ordered latent class model with infinite classes using a stochastic process prior. Furthermore, a nonparametric IRT application is also discussed.

ISBN: 9780438713000Subjects--Topical Terms:

3168483
Educational tests & measurements.
Subjects--Index Terms:

Bayesian methods

Three Contributions to Latent Variable Modeling.
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245 1 0 $a Three Contributions to Latent Variable Modeling.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 117 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-06, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: DeCarlo, Lawrence.
502 $a Thesis (Ph.D.)--Columbia University, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a The dissertation includes three papers that address some theoretical and technical issues of latent variable models. The first paper extends the uniformly most powerful test approach for testing person parameter in IRT to the two-parameter logistic models. In addition, an efficient branch-and-bound algorithm for computing the exact p-value is proposed. The second paper proposes a reparameterization of the log-linear CDM model. A Gibbs sampler is developed for posterior computation. The third paper proposes an ordered latent class model with infinite classes using a stochastic process prior. Furthermore, a nonparametric IRT application is also discussed.
590 $a School code: 0054.
650 4 $a Educational tests & measurements. $3 3168483
650 4 $a Statistics. $3 517247
650 4 $a Quantitative psychology. $3 2144748
653 $a Bayesian methods
653 $a Cognitive diagnostic models
653 $a Interval estimation
653 $a Item response theory
653 $a Ordered latent class models
653 $a Statistical inference
690 $a 0288
690 $a 0463
690 $a 0632
710 2 $a Columbia University. $b TC: Measurement and Evaluation. $3 3194606
773 0 $t Dissertations Abstracts International $g 80-06B.
790 $a 0054
791 $a Ph.D.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13420118