Structural equation modeling : applications using Mplus /

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Bibliographic Details
Author / Creator:Wang, Jichuan, author.
Edition:Second edition.
Imprint:Hoboken, NJ : Wiley, 2020.
©2020
Description:1 online resource (x, 512 pages)
Language:English
Series:Wiley series in probability and statistics
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/13677132
Hidden Bibliographic Details
Other authors / contributors:Wang, Xiaoqian, author.
ISBN:9781119422723
1119422728
9781119422716
111942271X
9781119422730
1119422736
9781119422709
Notes:Includes bibliographical references and index.
Online resource; title from digital title page (viewed on January 10, 2020).
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"--
Other form:Print version: Wang, Jichuan. Structural equation modeling. 2 edition. Hoboken, NJ : Wiley, 2020 9781119422709

MARC

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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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