Longitudinal structural equation modeling with Mplus : a latent state-trait perspective

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Titel
Longitudinal structural equation modeling with Mplus a latent state-trait perspective
verantwortlich
Geiser, Christian (VerfasserIn)
veröffentlicht
New York, London: The Guilford Press, [2021]
© 2021
Erscheinungsjahr
2021
Teil von
Methodology in the social sciences
Erscheint auch als
Geiser, Christian, 1978 - , Longitudinal structural equation modeling with Mplus, New York : The Guilford Press, 2021, xxiii, 344 Seiten
Andere Ausgaben
Longitudinal structural equation modeling with Mplus: a latent state-trait perspective
Andere Ausgaben
Longitudinal structural equation modeling with Mplus: a latent state-trait perspective
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author Geiser, Christian
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contents Cover -- Half Title Page -- Series Page -- Title Page -- Copyright -- Series Editor's Note -- Preface -- Brief Contents -- List of Abbreviations -- Guide to Statistical Symbols -- 1. A Measurement Theoretical Framework for Longitudinal Data: Introduction to Latent State-Trait Theory -- 2. Single-Factor Longitudinal Models for Single-Indicator Data -- 3. Multifactor Longitudinal Models for Single-Indicator Data -- 4. Latent State Models and Measurement Equivalence Testing in Longitudinal Studies -- 5. Multiple-Indicator Longitudinal Models -- 6. Modeling Intensive Longitudinal Data -- 7. Missing Data Handling -- 8. How to Choose between Models and Report the Results -- Extended Contents -- List of Abbreviations -- Guide to Statistical Symbols -- 1. A Measurement Theoretical Framework for Longitudinal Data: Introduction to Latent State-Trait Theory -- 1.1 Introduction -- 1.2 Latent State-Trait Theory -- 1.2.1 Introduction -- 1.2.2 Basic Idea -- 1.2.3 Random Experiment -- 1.2.4 Variables in LST-R Theory -- BOX 1.1. Key Concepts and Definitions in CTT -- 1.2.5 Properties -- 1.2.6 Coefficients -- BOX 1.2. Properties of the Latent Variables in LST-R Theory -- 1.3 Chapter Summary -- 1.4 Recommended Readings -- 2. Single-Factor Longitudinal Models for Single-Indicator Data -- 2.1 Introduction -- 2.2 The Random Intercept Model -- 2.2.1 Introduction -- 2.2.2 Model Description -- BOX 2.1. Available Information, Model Degrees of Freedom, and Model Identification in Single-Indicator Longitudinal Designs -- BOX 2.2. Defining the Random Intercept Model Based on LST-R Theory -- 2.2.3 Variance Decomposition and Reliability Coefficient -- 2.2.4 Mplus Application -- BOX 2.3. Model Fit Assessment and Model Comparisons -- 2.2.5 Summary -- 2.3 The Random and Fixed Intercepts Model -- 2.3.1 Introduction -- 2.3.2 Model Description.
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spelling 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, New York London The Guilford Press [2021], © 2021, 1 Online-Ressource (xxiii, 344 Seiten), Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, Methodology in the social sciences, Description based on publisher supplied metadata and other sources, Cover -- Half Title Page -- Series Page -- Title Page -- Copyright -- Series Editor's Note -- Preface -- Brief Contents -- List of Abbreviations -- Guide to Statistical Symbols -- 1. A Measurement Theoretical Framework for Longitudinal Data: Introduction to Latent State-Trait Theory -- 2. Single-Factor Longitudinal Models for Single-Indicator Data -- 3. Multifactor Longitudinal Models for Single-Indicator Data -- 4. Latent State Models and Measurement Equivalence Testing in Longitudinal Studies -- 5. Multiple-Indicator Longitudinal Models -- 6. Modeling Intensive Longitudinal Data -- 7. Missing Data Handling -- 8. How to Choose between Models and Report the Results -- Extended Contents -- List of Abbreviations -- Guide to Statistical Symbols -- 1. A Measurement Theoretical Framework for Longitudinal Data: Introduction to Latent State-Trait Theory -- 1.1 Introduction -- 1.2 Latent State-Trait Theory -- 1.2.1 Introduction -- 1.2.2 Basic Idea -- 1.2.3 Random Experiment -- 1.2.4 Variables in LST-R Theory -- BOX 1.1. Key Concepts and Definitions in CTT -- 1.2.5 Properties -- 1.2.6 Coefficients -- BOX 1.2. Properties of the Latent Variables in LST-R Theory -- 1.3 Chapter Summary -- 1.4 Recommended Readings -- 2. Single-Factor Longitudinal Models for Single-Indicator Data -- 2.1 Introduction -- 2.2 The Random Intercept Model -- 2.2.1 Introduction -- 2.2.2 Model Description -- BOX 2.1. Available Information, Model Degrees of Freedom, and Model Identification in Single-Indicator Longitudinal Designs -- BOX 2.2. Defining the Random Intercept Model Based on LST-R Theory -- 2.2.3 Variance Decomposition and Reliability Coefficient -- 2.2.4 Mplus Application -- BOX 2.3. Model Fit Assessment and Model Comparisons -- 2.2.5 Summary -- 2.3 The Random and Fixed Intercepts Model -- 2.3.1 Introduction -- 2.3.2 Model Description., Electronic books, 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), 9781462544240 hardcover, 9781462538782 paperback, Erscheint auch als Druck-Ausgabe Geiser, Christian, 1978 - Longitudinal structural equation modeling with Mplus New York : The Guilford Press, 2021 xxiii, 344 Seiten (DE-627)1742574521 9781462538782 9781462544240, https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=6336106 X:EBC Aggregator lizenzpflichtig
spellingShingle Geiser, Christian, Longitudinal structural equation modeling with Mplus: a latent state-trait perspective, Cover -- Half Title Page -- Series Page -- Title Page -- Copyright -- Series Editor's Note -- Preface -- Brief Contents -- List of Abbreviations -- Guide to Statistical Symbols -- 1. A Measurement Theoretical Framework for Longitudinal Data: Introduction to Latent State-Trait Theory -- 2. Single-Factor Longitudinal Models for Single-Indicator Data -- 3. Multifactor Longitudinal Models for Single-Indicator Data -- 4. Latent State Models and Measurement Equivalence Testing in Longitudinal Studies -- 5. Multiple-Indicator Longitudinal Models -- 6. Modeling Intensive Longitudinal Data -- 7. Missing Data Handling -- 8. How to Choose between Models and Report the Results -- Extended Contents -- List of Abbreviations -- Guide to Statistical Symbols -- 1. A Measurement Theoretical Framework for Longitudinal Data: Introduction to Latent State-Trait Theory -- 1.1 Introduction -- 1.2 Latent State-Trait Theory -- 1.2.1 Introduction -- 1.2.2 Basic Idea -- 1.2.3 Random Experiment -- 1.2.4 Variables in LST-R Theory -- BOX 1.1. Key Concepts and Definitions in CTT -- 1.2.5 Properties -- 1.2.6 Coefficients -- BOX 1.2. Properties of the Latent Variables in LST-R Theory -- 1.3 Chapter Summary -- 1.4 Recommended Readings -- 2. Single-Factor Longitudinal Models for Single-Indicator Data -- 2.1 Introduction -- 2.2 The Random Intercept Model -- 2.2.1 Introduction -- 2.2.2 Model Description -- BOX 2.1. Available Information, Model Degrees of Freedom, and Model Identification in Single-Indicator Longitudinal Designs -- BOX 2.2. Defining the Random Intercept Model Based on LST-R Theory -- 2.2.3 Variance Decomposition and Reliability Coefficient -- 2.2.4 Mplus Application -- BOX 2.3. Model Fit Assessment and Model Comparisons -- 2.2.5 Summary -- 2.3 The Random and Fixed Intercepts Model -- 2.3.1 Introduction -- 2.3.2 Model Description., Electronic books, Mplus, Strukturgleichungsmodell, Längsschnittuntersuchung, 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
title_fullStr Longitudinal structural equation modeling with Mplus a latent state-trait perspective Christian Geiser
title_full_unstemmed Longitudinal structural equation modeling with Mplus a latent state-trait perspective Christian Geiser
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 Electronic books, Mplus, Strukturgleichungsmodell, Längsschnittuntersuchung, Faktorenanalyse
topic_facet Electronic books, Mplus, Strukturgleichungsmodell, Längsschnittuntersuchung, Faktorenanalyse
url https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=6336106
work_keys_str_mv AT geiserchristian longitudinalstructuralequationmodelingwithmplusalatentstatetraitperspective