Structural Equation Modeling

Structural Equation Modeling
Author : Jichuan Wang
Publisher : John Wiley & Sons
Total Pages : 534
Release : 2019-12-04
ISBN 10 : 9781119422709
ISBN 13 : 1119422701
Language : EN, FR, DE, ES & NL

Structural Equation Modeling Book Description:

Presents a useful guide for applications of SEM whilst systematically demonstrating various SEM models using Mplus Focusing on the conceptual and practical aspects of Structural Equation Modeling (SEM), this book demonstrates basic concepts and examples of various SEM models, along with updates on many advanced methods, including confirmatory factor analysis (CFA) with categorical items, bifactor model, Bayesian CFA model, item response theory (IRT) model, graded response model (GRM), multiple imputation (MI) of missing values, plausible values of latent variables, moderated mediation model, Bayesian SEM, latent growth modeling (LGM) with individually varying times of observations, dynamic structural equation modeling (DSEM), residual dynamic structural equation modeling (RDSEM), testing measurement invariance of instrument with categorical variables, longitudinal latent class analysis (LLCA), latent transition analysis (LTA), growth mixture modeling (GMM) with covariates and distal outcome, manual implementation of the BCH method and the three-step method for mixture modeling, Monte Carlo simulation power analysis for various SEM models, and estimate sample size for latent class analysis (LCA) model. The statistical modeling program Mplus Version 8.2 is featured with all models updated. It provides researchers with a flexible tool that allows them to analyze data with an easy-to-use interface and graphical displays of data and analysis results. Intended as both a teaching resource and a reference guide, and written in non-mathematical terms, Structural Equation Modeling: Applications Using Mplus, 2nd edition provides step-by-step instructions of model specification, estimation, evaluation, and modification. Chapters cover: Confirmatory Factor Analysis (CFA); Structural Equation Models (SEM); SEM for Longitudinal Data; Multi-Group Models; Mixture Models; and Power Analysis and Sample Size Estimate for SEM. Presents a useful reference guide for applications of SEM while systematically demonstrating various advanced SEM models Discusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes Provides step-by-step instructions of model specification and estimation, as well as detailed interpretation of Mplus results using real data sets Introduces different methods for sample size estimate and statistical power analysis for SEM Structural Equation Modeling is an excellent book for researchers and graduate students of SEM who want to understand the theory and learn how to build their own SEM models using Mplus.

Using Mplus for Structural Equation Modeling
Language: en
Pages: 249
Authors: E. Kevin Kelloway
Categories: Social Science
Type: BOOK - Published: 2014-07-22 - Publisher: SAGE Publications

Ideal for researchers and graduate students in the social sciences who require knowledge of structural equation modeling techniques to answer substantive resear
Structural Equation Modeling
Language: en
Pages: 534
Authors: Jichuan Wang
Categories: Mathematics
Type: BOOK - Published: 2019-12-04 - Publisher: John Wiley & Sons

Presents a useful guide for applications of SEM whilst systematically demonstrating various SEM models using Mplus Focusing on the conceptual and practical aspe
Multilevel Modeling Using Mplus
Language: en
Pages: 341
Authors: Holmes Finch
Categories:
Type: BOOK - Published: 2017-01 - Publisher: Chapman & Hall/CRC

This book is designed primarily for upper level undergraduate and graduate level students taking a course in multilevel modelling and/or statistical modelling w
Structural Equation Modeling
Language: en
Pages: 536
Authors: Jichuan Wang
Categories: Mathematics
Type: BOOK - Published: 2019-09-17 - Publisher: John Wiley & Sons

Presents a useful guide for applications of SEM whilst systematically demonstrating various SEM models using Mplus Focusing on the conceptual and practical aspe
Structural Equation Modeling with Mplus
Language: en
Pages: 432
Authors: Barbara M. Byrne
Categories: Business & Economics
Type: BOOK - Published: 2013-06-17 - Publisher: Routledge

"This text aims to provide readers with a nonmathematical introduction to the basic concepts associated with structural equation modeling, and to illustrate its
Longitudinal Structural Equation Modeling with Mplus
Language: en
Pages: 370
Authors: Christian Geiser
Categories: Business & Economics
Type: BOOK - Published: 2020-10-08 - Publisher: Guilford Publications

An in-depth guide to executing longitudinal confirmatory factor analysis (CFA) and structural equation modeling (SEM) in Mplus, this book uses latent state–tr
Structural Equation Modeling with Mplus
Language: en
Pages: 412
Authors: Barbara M. Byrne
Categories: Education
Type: BOOK - Published: 2012 - Publisher: Routledge Academic

"This text aims to provide readers with a nonmathematical introduction to the basic concepts associated with structural equation modeling, and to illustrate its
Structural Equation Modeling
Language: en
Pages: 500
Authors: Xiaoqian Wang
Categories: Social Science
Type: BOOK - Published: 2012-07-31 - Publisher: John Wiley & Sons

A reference guide for applications of SEM using Mplus Structural Equation Modeling: Applications Using Mplus is intended as both a teaching resource and a refer
Handbook of Structural Equation Modeling
Language: en
Pages: 801
Authors: Rick H. Hoyle
Categories: Business & Economics
Type: BOOK - Published: 2023-02-17 - Publisher: Guilford Publications

"This accessible volume presents both the mechanics of structural equation modeling (SEM) and specific SEM strategies and applications. The editor, along with a
Structural Equation Modeling for Health and Medicine
Language: en
Pages: 318
Authors: Douglas D. Gunzler
Categories: Mathematics
Type: BOOK - Published: 2021-04-12 - Publisher: CRC Press

Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of