Literaturnachweis - Detailanzeige
Autor/in | Geiser, Christian |
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Sonst. Personen | Little, Todd D. (Geleitw.) |
Titel | Longitudinal structural equation modeling with Mplus. A latent state-trait perspective. |
Quelle | New York; London: The Guilford Press (2021), xxiii, 344 S. |
Reihe | Methodology in the social sciences |
Beigaben | Illustrationen; Diagramme; Literaturangaben |
Zusatzinformation | Inhaltsverzeichnis |
Sprache | englisch |
Dokumenttyp | gedruckt; Monographie |
ISBN | 978-1-4625-3878-2; 978-1-4625-4424-0 |
Schlagwörter | Faktorenanalyse; Längsschnittuntersuchung; Methodologie; Reliabilität; Strukturgleichungsmodell; Sozialforschung; Datenanalyse; Sozialwissenschaften; Statistik; Daten; Forschungsdaten; Modellierung |
Abstract | 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. (DIPF/Orig.). |
Erfasst von | DIPF | Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main |
Update | 2023/1 |