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"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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Geiser, Christian 1978- VerfasserIn (DE-588)13650082X (DE-627)595584918 (DE-576)288290615 aut, Longitudinal structural equation modeling with Mplus a latent state-trait perspective Christian Geiser ; series editor's note by Todd D. Little, New York London The Guilford Press [2021], © 2021, xxiii, 344 Seiten Illustrationen, Diagramme, Text txt rdacontent, ohne Hilfsmittel zu benutzen n rdamedia, Band nc rdacarrier, Methodology in the social sciences, Literaturangaben, "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"--, Mplus, Longitudinal method, Structural equation modeling, (DE-588)4123037-1 (DE-627)105758051 (DE-576)209556331 Datenanalyse gnd, (DE-588)4034036-3 (DE-627)104682779 (DE-576)209004711 Längsschnittuntersuchung gnd, (DE-588)7716737-5 (DE-627)635554496 (DE-576)330177184 Mplus gnd, (DE-588)4192516-6 (DE-627)105233951 (DE-576)210081082 Datenmodell gnd, (DE-588)1271364182 (DE-627)1820177084 Datenmodellierung gnd, s (DE-588)7716737-5 (DE-627)635554496 (DE-576)330177184 Mplus gnd, s (DE-588)4252999-2 (DE-627)10435755X (DE-576)210527501 Strukturgleichungsmodell gnd, s (DE-588)4034036-3 (DE-627)104682779 (DE-576)209004711 Längsschnittuntersuchung gnd, s (DE-588)4016338-6 (DE-627)104589760 (DE-576)208915567 Faktorenanalyse gnd, (DE-627), Little, Todd D. 1960- VerfasserIn eines Geleitwortes (DE-588)1038167000 (DE-627)756724406 (DE-576)174343612 aui, Erscheint auch als Online-Ausgabe Geiser, Christian, 1978 - Longitudinal structural equation modeling with Mplus New York : The Guilford Press, 2021 1 Online-Ressource (xxiii, 344 Seiten) (DE-627)1733136649 9781462544264, https://www.gbv.de/dms/bowker/toc/9781462538782.pdf 2021-10-20 Aggregator Inhaltsverzeichnis |
| spellingShingle |
Geiser, Christian, Longitudinal structural equation modeling with Mplus: a latent state-trait perspective, "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"--, Mplus, Longitudinal method, Structural equation modeling, Datenanalyse, Längsschnittuntersuchung, Datenmodell, Datenmodellierung, Strukturgleichungsmodell, Faktorenanalyse |
| title |
Longitudinal structural equation modeling with Mplus: a latent state-trait perspective |
| title_auth |
Longitudinal structural equation modeling with Mplus a latent state-trait perspective |
| title_full |
Longitudinal structural equation modeling with Mplus a latent state-trait perspective Christian Geiser ; series editor's note by Todd D. Little |
| title_fullStr |
Longitudinal structural equation modeling with Mplus a latent state-trait perspective Christian Geiser ; series editor's note by Todd D. Little |
| title_full_unstemmed |
Longitudinal structural equation modeling with Mplus a latent state-trait perspective Christian Geiser ; series editor's note by Todd D. Little |
| title_short |
Longitudinal structural equation modeling with Mplus |
| title_sort |
longitudinal structural equation modeling with mplus a latent state-trait perspective |
| title_sub |
a latent state-trait perspective |
| title_unstemmed |
Longitudinal structural equation modeling with Mplus: a latent state-trait perspective |
| topic |
Mplus, Longitudinal method, Structural equation modeling, Datenanalyse, Längsschnittuntersuchung, Datenmodell, Datenmodellierung, Strukturgleichungsmodell, Faktorenanalyse |
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Mplus, Longitudinal method, Structural equation modeling, Datenanalyse, Längsschnittuntersuchung, Datenmodell, Datenmodellierung, Strukturgleichungsmodell, Faktorenanalyse |
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