Item factor analysis: current approaches and future directions.

Item factor analysis: current approaches and future directions. Research Abstract Details 

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Item factor analysis: current approaches and future directions. Abstract Text:

R J Wirth,Michael C Edwards,

The rationale underlying factor analysis applies to continuous and categorical variables alike; however, the models and estimation methods for continuous (i.e., interval or ratio scale) data are not appropriate for item-level data that are categorical in nature. The authors provide a targeted review and synthesis of the item factor analysis (IFA) estimation literature for ordered-categorical data (e.g., Likert-type response scales) with specific attention paid to the problems of estimating models with many items and many factors. Popular IFA models and estimation methods found in the structural equation modeling and item response theory literatures are presented. Following this presentation, recent developments in the estimation of IFA parameters (e.g., Markov chain Monte Carlo) are discussed. The authors conclude with considerations for future research on IFA, simulated examples, and advice for applied researchers.

Item factor analysis: current approaches and future directions. Publishing Authors By Initials

RJ Wirth,MC Edwards,

For similar behavioral disciplines and activities: behavioral sciences: psychology research abstracts see: behavioral disciplines and activities: behavioral sciences: psychology research

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Item factor analysis: current approaches and future directions. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: Psychological methods

VOLUME: 12

Page Numbers: 58-79

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ISSN: 1082-989X

DAY: 3

MONTH: Mar

YEAR: 2007

Item factor analysis: current approaches and future directions. Information

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LANGUAGE: eng

NlmUniqueID: 9606928

Item factor analysis: current approaches and future directions. Keywords Mesh Terms:

KEYWORDS: Psychology

MESH TERMS: trends

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Grant and Affiliation Information for Item factor analysis: current approaches and future directions.

AFFILIATION: L. L. Thurstone Psychometric Laboratory, Department of Psychology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3270, USA. rjwirth@unc.edu

Country: United States

AGENCY: United States NIDA

GRANT: R01DA015398

ACRONYM: DA

MEDLINETA: Psychol Methods

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