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Article: A Direct Estimation Method on Analyzing Ipsative Data With Chan and Bentlers (1993) Method

TitleA Direct Estimation Method on Analyzing Ipsative Data With Chan and Bentlers (1993) Method
Authors
Issue Date2004
PublisherLawrence Erlbaum Associates, Inc. The Journal's web site is located at http://www.leaonline.com/loi/sem
Citation
Structural Equation Modeling, 2004, v. 11 n. 2, p. 217-243 How to Cite?
AbstractIpsative data (individual scores subject to a constant-sum constraint), suggested to minimize response bias, are sometimes observed in behavioral sciences. Chan and Bentler (1993, 1996) proposed a method to analyze ipsative data in a single-group case. Cheung and Chan (2002) extended the method to multiple-group analysis. However, these methods require tedious procedures on formulating within- and between- group constraints and recovering the parameter estimates and their standard errors. A direct estimation method, which is equivalent to Chan and Bender's method with an alternative model specification, is proposed in this article. The 1st-order factor-analytic ipsative model in Chan and Bentler's method is reparameterized as a restricted 2nd-order factor-analytic model with fixed factor loading matrix reflecting the ipsative properties in the direct estimation method. The direct estimation method can be easily extended to test measurement invariance properties in multiple-group analysis. Issues related to ipsative models are also addressed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Persistent Identifierhttp://hdl.handle.net/10722/224183
ISSN
2021 Impact Factor: 6.181
2020 SCImago Journal Rankings: 4.041
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorCheung, MWL-
dc.date.accessioned2016-03-29T04:38:01Z-
dc.date.available2016-03-29T04:38:01Z-
dc.date.issued2004-
dc.identifier.citationStructural Equation Modeling, 2004, v. 11 n. 2, p. 217-243-
dc.identifier.issn1070-5511-
dc.identifier.urihttp://hdl.handle.net/10722/224183-
dc.description.abstractIpsative data (individual scores subject to a constant-sum constraint), suggested to minimize response bias, are sometimes observed in behavioral sciences. Chan and Bentler (1993, 1996) proposed a method to analyze ipsative data in a single-group case. Cheung and Chan (2002) extended the method to multiple-group analysis. However, these methods require tedious procedures on formulating within- and between- group constraints and recovering the parameter estimates and their standard errors. A direct estimation method, which is equivalent to Chan and Bender's method with an alternative model specification, is proposed in this article. The 1st-order factor-analytic ipsative model in Chan and Bentler's method is reparameterized as a restricted 2nd-order factor-analytic model with fixed factor loading matrix reflecting the ipsative properties in the direct estimation method. The direct estimation method can be easily extended to test measurement invariance properties in multiple-group analysis. Issues related to ipsative models are also addressed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)-
dc.languageeng-
dc.publisherLawrence Erlbaum Associates, Inc. The Journal's web site is located at http://www.leaonline.com/loi/sem-
dc.relation.ispartofStructural Equation Modeling-
dc.rightsPreprint: This is an Author's Original Manuscript of an article published by Taylor & Francis Group in [JOURNAL TITLE] on [date of publication], available online: http://www.tandfonline.com/doi/abs/[Article DOI]. Postprint: This is an Accepted Manuscript of an article published by Taylor & Francis Group in [JOURNAL TITLE] on [date of publication], available online at: http://www.tandfonline.com/doi/abs/[Article DOI]. -
dc.titleA Direct Estimation Method on Analyzing Ipsative Data With Chan and Bentlers (1993) Method-
dc.typeArticle-
dc.identifier.doi10.1207/s15328007sem1102_5-
dc.identifier.scopuseid_2-s2.0-2642554765-
dc.identifier.hkuros89770-
dc.identifier.volume11-
dc.identifier.issue2-
dc.identifier.spage217-
dc.identifier.epage243-
dc.identifier.isiWOS:000221805000005-
dc.publisher.placeUnited States-
dc.identifier.issnl1070-5511-

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