Indira Gandhi National Tribal University, Amarkantak

Prof. Ram Dayal Munda Central Library

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Structural equation modeling : applications using Mplus / Jichuan Wang, Xiaoqian Wang.

By: Contributor(s): Material type: TextTextSeries: Wiley series in probability and statisticsPublisher: Hoboken, NJ : Wiley, 2020Copyright date: ©2020Edition: Second editionDescription: 1 online resource (x, 512 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781119422723
  • 1119422728
  • 9781119422716
  • 111942271X
Subject(s): Genre/Form: Additional physical formats: Print version:: Structural equation modelingDDC classification:
  • 519.5/3 23
LOC classification:
  • QA278.3 .W36 2020
Online resources:
Contents:
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.
Summary: 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"-- Provided by publisher.
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Includes bibliographical references and index.

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.

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"-- Provided by publisher.

Description based on online resource; title from digital title page (viewed on January 10, 2020).

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