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Confirmatory factor analysis for applied research / Timothy A. Brown.

By: Series: Methodology in the social sciencesPublisher: New York : The Guilford Press, [2015]Copyright date: ©2015Edition: Second editionDescription: xvii, 462 pages ; 26 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781462517794
  • 146251779X
  • 9781462515363
  • 1462515363
Subject(s):
Contents:
The common factor model and exploratory factor analysis -- Introduction to CFA -- Specification and interpretation of CFA models -- Model revision and comparison -- CFA of multitrait-multimethod matrices -- CFA with equality constraints, multiple groups, and mean structures -- Other types of CFA models : higher-order factor analysis, scale reliability evaluation, and formative indicators -- Data issues in CFA : missing, non-normal, and categorical data -- Statistical power and sample size -- recent developments involving CFA models.
Summary: 'With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website offers data and program syntax files for most of the research examples, as well as links to CFA-related resources. New to This Edition *Updated throughout to incorporate important developments in latent variable modeling. *Chapter on Bayesian CFA and multilevel measurement models. *Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables. *Utilizes the latest versions of major latent variable software packages'-- Provided by publisher.
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Item type Current library Home library Call number Materials specified Copy number Status Date due Barcode
AM PERPUSTAKAAN TUN SERI LANANG PERPUSTAKAAN TUN SERI LANANG KOLEKSI AM-P. TUN SERI LANANG (ARAS 5) QA278.5.B766 2015 (Browse shelf(Opens below)) 1 Available 00002154202

Includes bibliographical references and index.

The common factor model and exploratory factor analysis -- Introduction to CFA -- Specification and interpretation of CFA models -- Model revision and comparison -- CFA of multitrait-multimethod matrices -- CFA with equality constraints, multiple groups, and mean structures -- Other types of CFA models : higher-order factor analysis, scale reliability evaluation, and formative indicators -- Data issues in CFA : missing, non-normal, and categorical data -- Statistical power and sample size -- recent developments involving CFA models.

'With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website offers data and program syntax files for most of the research examples, as well as links to CFA-related resources. New to This Edition *Updated throughout to incorporate important developments in latent variable modeling. *Chapter on Bayesian CFA and multilevel measurement models. *Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables. *Utilizes the latest versions of major latent variable software packages'-- Provided by publisher.

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