東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Three-way interactions with latent v...

The University of North Carolina at Chapel Hill., Psychology.

Linked to FindBook

Google Book

Amazon

博客來

Three-way interactions with latent variables: A maximum likelihood approach.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Three-way interactions with latent variables: A maximum likelihood approach./
Author:	Huang, Wenjing.
Description:	60 p.
Notes:	Adviser: Patrick J. Curran.
Contained By:	Masters Abstracts International47-01.
Subject:	Psychology, Psychometrics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1454425
ISBN:	9780549668411

Three-way interactions with latent variables: A maximum likelihood approach.
Huang, Wenjing.

Three-way interactions with latent variables: A maximum likelihood approach. - 60 p.

Adviser: Patrick J. Curran.

Thesis (M.A.)--The University of North Carolina at Chapel Hill, 2008.

Two-way interaction in latent variables has been a topic of considerable theoretical and practical interest among psychological methodologists. Since the seminal work of Kenny and Judd (1984), much research has focused on the use of product indicators for the estimation of latent moderation effects. These methods are usually difficult to use, and many popular approaches lack solid statistical justification. In recent years, the development of full-information maximum likelihood for nonlinear latent variables models provided a new approach to the estimation of latent variable interaction effects. However, a particular kind of three-way interaction, i.e., two-way latent variable interactions over an observed grouping variable, has received little attention. In this thesis, existing literature is reviewed and studied to arrive at a derivation of the full-information maximum likelihood estimator for three-way interactions in latent variables. It is also shown that this new method of estimation and testing can be implemented in Mplus (Muthen & Muthen, 1998--2007) using mixture modelling. To study the properties of this new estimation method, a simulation study is conducted, and the new method is shown to have superior performance than an existing method proposed by Marsh, Wen, and Hau (2004).

ISBN: 9780549668411Subjects--Topical Terms:

1017742
Psychology, Psychometrics.

Three-way interactions with latent variables: A maximum likelihood approach.
LDR:02348nmm 2200313 a 45 001 891370
005 20101111
008 101111s2008 ||||||||||||||||| ||eng d
020 $a 9780549668411
035 $a (UMI)AAI1454425
035 $a AAI1454425
040 $a UMI $c UMI
100 1 $a Huang, Wenjing. $3 1065365
245 1 0 $a Three-way interactions with latent variables: A maximum likelihood approach.
300 $a 60 p.
500 $a Adviser: Patrick J. Curran.
500 $a Source: Masters Abstracts International, Volume: 47-01, page: 0614.
502 $a Thesis (M.A.)--The University of North Carolina at Chapel Hill, 2008.
520 $a Two-way interaction in latent variables has been a topic of considerable theoretical and practical interest among psychological methodologists. Since the seminal work of Kenny and Judd (1984), much research has focused on the use of product indicators for the estimation of latent moderation effects. These methods are usually difficult to use, and many popular approaches lack solid statistical justification. In recent years, the development of full-information maximum likelihood for nonlinear latent variables models provided a new approach to the estimation of latent variable interaction effects. However, a particular kind of three-way interaction, i.e., two-way latent variable interactions over an observed grouping variable, has received little attention. In this thesis, existing literature is reviewed and studied to arrive at a derivation of the full-information maximum likelihood estimator for three-way interactions in latent variables. It is also shown that this new method of estimation and testing can be implemented in Mplus (Muthen & Muthen, 1998--2007) using mixture modelling. To study the properties of this new estimation method, a simulation study is conducted, and the new method is shown to have superior performance than an existing method proposed by Marsh, Wen, and Hau (2004).
590 $a School code: 0153.
650 4 $a Psychology, Psychometrics. $3 1017742
650 4 $a Statistics. $3 517247
690 $a 0463
690 $a 0632
710 2 $a The University of North Carolina at Chapel Hill. $b Psychology. $3 1017867
773 0 $t Masters Abstracts International $g 47-01.
790 $a 0153
790 1 0 $a Bauer, Daniel J. $e committee member
790 1 0 $a Curran, Patrick J. $e committee member
790 1 0 $a Curran, Patrick J., $e advisor
790 1 0 $a Hussong, Andrea M. $e committee member
791 $a M.A.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1454425