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Structural equation modeling : applications using Mplus /

Discusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes. Explores different methods for sample size estimate and statistical power analysis for SEM. By following the examples provided in this second edition, readers...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Wang, Jichuan (Autor), Wang, Xiaoqian (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, NJ : Wiley, 2020.
Edición:Second edition.
Colección:Wiley series in probability and statistics
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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245 1 0 |a Structural equation modeling :  |b applications using Mplus /  |c Jichuan Wang, Xiaoqian Wang. 
250 |a Second edition. 
264 1 |a Hoboken, NJ :  |b Wiley,  |c 2020. 
264 4 |c ©2020 
300 |a 1 online resource (x, 512 pages) 
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505 0 |a Confirmatory factor analysis -- Structural equation model -- Latent growth models (LGM) for longitudinal data analysis -- Multi-group modeling -- Mixture modeling -- Sample size for structural equation modeling. 
520 |a Discusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes. Explores different methods for sample size estimate and statistical power analysis for SEM. By following the examples provided in this second edition, readers will be able to build their own SEM models using Mplus. Teachers, graduate students, and researchers in social sciences and health studies will also benefit from this book"--  |c Provided by publisher 
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650 6 |a Modèles d'équations structurales  |x Informatique. 
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700 1 |a Wang, Xiaoqian,  |e author. 
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