An in-depth guide to executing longitudinal confirmatory factor analysis (CFA) and structural equation modeling (SEM) in Mplus, this book uses latent state–trait (LST) theory as a unifying conceptual framework, including the relevant coefficients of consistency, occasion specificity, and reliability. Following a standard format, chapters review the theoretical underpinnings, strengths, and limitations of the various models; present data examples; and demonstrate each model's application and interpretation in Mplus, with numerous screen shots and output excerpts. Coverage encompasses both traditional models (autoregressive, change score, and growth curve models) and LST models for analyzing single- and multiple-indicator data. The book discusses measurement equivalence testing, intensive longitudinal data modeling, and missing data handling, and provides strategies for model selection and reporting of results. User-friendly features include special-topic boxes, chapter summaries, and suggestions for further reading. The companion website features data sets, annotated syntax files, and output for all of the examples.
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Christian Geiser, PhD, is a former professor of quantitative psychology. He currently works as an instructor and statistical consultant. His areas of expertise are in structural equation modeling, longitudinal data analysis, latent class modeling, multitrait–multimethod analysis, and measurement. His website is https://christiangeiser.com/.
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Da: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Paperback. Condizione: Good. An in-depth guide to executing longitudinal confirmatory factor analysis (CFA) and structural equation modeling (SEM) in Mplus, this book uses latent statetrait (LST) theory as a unifying conceptual framework, including the relevant coefficients of consistency, occasion specificity, and reliability. Codice articolo 00109064237
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Da: World of Books Inc, Montgomery, IL, U.S.A.
Paperback. Condizione: Good. An in-depth guide to executing longitudinal confirmatory factor analysis (CFA) and structural equation modeling (SEM) in Mplus, this book uses latent statetrait (LST) theory as a unifying conceptual framework, including the relevant coefficients of consistency, occasion specificity, and reliability. Codice articolo CIN1462538789G
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Softcover/Paperback. Condizione: Gut. 344 p. Good. Ex-library with usual markings. Clean pages. Sprache: Englisch Gewicht in Gramm: 600. Codice articolo 895259
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Paperback. Condizione: New. An in-depth guide to executing longitudinal confirmatory factor analysis (CFA) and structural equation modeling (SEM) in Mplus, this book uses latent state-trait (LST) theory as a unifying conceptual framework, including the relevant coefficients of consistency, occasion specificity, and reliability. Following a standard format, chapters review the theoretical underpinnings, strengths, and limitations of the various models; present data examples; and demonstrate each model's application and interpretation in Mplus, with numerous screen shots and output excerpts. Coverage encompasses both traditional models (autoregressive, change score, and growth curve models) and LST models for analyzing single- and multiple-indicator data. The book discusses measurement equivalence testing, intensive longitudinal data modeling, and missing data handling, and provides strategies for model selection and reporting of results. User-friendly features include special-topic boxes, chapter summaries, and suggestions for further reading. The companion website features data sets, annotated syntax files, and output for all of the examples. Codice articolo LU-9781462538782
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Condizione: New. 2020. 1st Edition. Paperback. . . . . . Codice articolo V9781462538782
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Condizione: As New. Unread book in perfect condition. Codice articolo 41227601
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