You are in: Asia
Change location

You are here

Book > Textbooks > Research Methods in Psychology

Disable VAT on Taiwan

Unfortunately, as of 1 January 2020 SAGE Ltd is no longer able to support sales of electronically supplied services to Taiwan customers that are not Taiwan VAT registered. We apologise for any inconvenience. For more information or to place a print-only order, please contact uk.customerservices@sagepub.co.uk.

Using Mplus for Structural Equation Modeling
Share
Share

Using Mplus for Structural Equation Modeling
A Researcher's Guide

Second Edition
September 2014 | 248 pages | SAGE Publications, Inc
Download flyer

Ideal for researchers and graduate students in the social sciences who require knowledge of structural equation modeling techniques to answer substantive research questions, Using Mplus for Structural Equation Modeling provides a reader-friendly introduction to the major types of structural equation models implemented in the Mplus framework. This practical book, which updates author E. Kevin Kelloway’s 1998 book Using LISREL for Structural Equation Modeling, retains the successful five-step process employed in the earlier book, with a thorough update for use in the Mplus environment. Kelloway provides an overview of structural equation modeling techniques in Mplus, including the estimation of confirmatory factor analysis and observed variable path analysis. He also covers multilevel modeling for hypothesis testing in real life settings and offers an introduction to the extended capabilities of Mplus, such as exploratory structural equation modeling and estimation and testing of mediated relationships. A sample application with the source code, printout, and results is presented for each type of analysis.

 
Chapter 1: Introduction
Why Structural Equation Modeling?

 
The Remainder of This Book

 
 
Chapter 2: Structural Equation Models: Theory and Development
The Process of Structural Equation Modeling

 
 
Chapter 3: Assessing Model Fit
Absolute Fit

 
Comparative Fit

 
Parsimonious Fit

 
Toward a Strategy for Assessing Model Fit

 
 
Chapter 4: Using MPlus
The Data File

 
The Command File

 
Putting It All Together: Some Basic Analyses

 
 
Chapter 5: Confirmatory Factor Analysis
Model Specification

 
Identification

 
Estimation

 
Assessment of Fit

 
Model Modification

 
Sample Results Section

 
 
Chapter 6: Observed Variable Path Analysis
Model Specification

 
Identification

 
Estimation

 
Mediation

 
Using Equality Constraints

 
Multisample Analysis

 
 
Chapter 7: Latent Variable Path Analysis
Model Specification

 
Sample Results

 
 
Chapter 8: Longitudinal Analysis
Measurement Equivalence Across Time

 
Latent Growth Curves

 
Cross-Lagged Models

 
 
Chapter 9: Multilevel Modeling
Multilevel Models in Mplus

 
Conditional Models

 
Random-Slope Models

 
Multilevel Modeling and Mediation

 

Supplements

Data Set Zip File
Data files that accompany the book are also available under the "Preview" tab above.

"An excellent book on the ins and outs of using Mplus, as well as the practice of structural equation modeling in applied research.”

Kevin J. Grimm, University of California, Davis

This textbook fits all my needs for teaching from basic to more advanced SEM techniques.
The text is easy to follow and the examples using real data are excellent. I strongly recommend this position!!

Dr Bruno Schivinski
Nottingham Business School, Nottingham Trent University
November 14, 2016
Report this review

The Author did a great with this textbook. The examples are easy to follow and the language is clear. Strongly recommended to those looking for applied SEM in context.

Dr Bruno Schivinski
Nottingham Business School, Nottingham Trent University
March 28, 2017
Report this review

Very useful book for students and practitioners who want to get an introduction into SEM with Mplus. It provides insight into some main analysis techniques and guides you step by step through necessary procedures when importing a dataset into Mplus.

Ms Yvon Van den Boer
Media, Communication & Organisation, Twente University
December 15, 2014
Report this review

Chapters of the multivariate analysis course

Dr Zhidong Zhang
Colg of Education, Univ Of Texas-Brownsville/Tsc
December 10, 2014
Report this review

Sample Materials & Chapters

Data Files

For instructors

Select a Purchasing Option

Related Products

Best Practices in Data Cleaning
Best Practices in Data Cleaning
Regression, ANOVA, and the General Linear Model
Regression, ANOVA, and the General Linear Model
Show More Show Less
SAGE Research Methods Promotion

SAGE Research Methods is a research methods tool created to help researchers, faculty and students with their research projects. SAGE Research Methods links over 175,000 pages of SAGE’s renowned book, journal and reference content with truly advanced search and discovery tools. Researchers can explore methods concepts to help them design research projects, understand particular methods or identify a new method, conduct their research, and write up their findings. Since SAGE Research Methods focuses on methodology rather than disciplines, it can be used across the social sciences, health sciences, and more.

With SAGE Research Methods, researchers can explore their chosen method across the depth and breadth of content, expanding or refining their search as needed; read online, print, or email full-text content; utilize suggested related methods and links to related authors from SAGE Research Methods' robust library and unique features; and even share their own collections of content through Methods Lists. SAGE Research Methods contains content from over 720 books, dictionaries, encyclopedias, and handbooks, the entire “Little Green Book,” and "Little Blue Book” series, two Major Works collating a selection of journal articles, and specially commissioned videos.

Find out more