
Contents
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Introduction Introduction
-
Structural Equation Models Defined Structural Equation Models Defined
-
Confirmatory Factor Analysis and the Popular LISREL Movement Confirmatory Factor Analysis and the Popular LISREL Movement
-
The Current Status of Structual Equation Model Research The Current Status of Structual Equation Model Research
-
Structural Equation Modeling As a Concept Structural Equation Modeling As a Concept
-
-
Using Path Analyses Diagrams Using Path Analyses Diagrams
-
Missing Predictor Biases in Regression Missing Predictor Biases in Regression
-
Bias Resulting From Unreliability of Predictors Bias Resulting From Unreliability of Predictors
-
Bias Resulting From Unreliability of Outcomes Bias Resulting From Unreliability of Outcomes
-
Bias Resulting From Unreliability in Both Predictors and Outcomes Bias Resulting From Unreliability in Both Predictors and Outcomes
-
Bias Resulting From True Feedback Loops Bias Resulting From True Feedback Loops
-
Additional Issues When Considering Both Means and Covariances Additional Issues When Considering Both Means and Covariances
-
-
Including Common Factors/Latent Variables in Models Including Common Factors/Latent Variables in Models
-
The Structure of Common Factor Models The Structure of Common Factor Models
-
The Structure of Common Factors Within Latent Path Regression The Structure of Common Factors Within Latent Path Regression
-
The Structure of Invariant Common Factors Over Time The Structure of Invariant Common Factors Over Time
-
The Structure of Common Factors for Multiple Repeated Measures The Structure of Common Factors for Multiple Repeated Measures
-
-
Structual Equation Modeling As a Tool Structual Equation Modeling As a Tool
-
Structural Equation Modeling As a General Data Analysis Technique Structural Equation Modeling As a General Data Analysis Technique
-
Creating Structural Equation Modeling Expectations Creating Structural Equation Modeling Expectations
-
Statistical Indicators in Structural Equation Modeling Statistical Indicators in Structural Equation Modeling
-
Structural Equation Modeling Estimation of Linear Multiple Regression Structural Equation Modeling Estimation of Linear Multiple Regression
-
-
Considering Common Factors/Latent Variables in Models Considering Common Factors/Latent Variables in Models
-
Considering Benefits and Limitations of Including Common Factors Considering Benefits and Limitations of Including Common Factors
-
Common Factors With Cross-Sectional Observations Common Factors With Cross-Sectional Observations
-
Common Factors With Longitudinal Observations Common Factors With Longitudinal Observations
-
Common Factors With Multiple Longitudinal Observations Common Factors With Multiple Longitudinal Observations
-
The Future of Structural Equation Modeling The Future of Structural Equation Modeling
-
Technical Appendix: Algebraic Notes and Computer Programs for the SEMs Presented Technical Appendix: Algebraic Notes and Computer Programs for the SEMs Presented
-
1. Reconsidering Simple Linear Regression 1. Reconsidering Simple Linear Regression
-
2. An Example of Structural Equation Model Fitting 2. An Example of Structural Equation Model Fitting
-
-
-
Fitting the Simulated MIMIC Data With Standard Modeling Software Fitting the Simulated MIMIC Data With Standard Modeling Software
-
Fitting the Simulated MIMIC Data With SEM-CALIS Fitting the Simulated MIMIC Data With SEM-CALIS
-
Fitting the Simulated MIMIC Data With SEM-Mplus Fitting the Simulated MIMIC Data With SEM-Mplus
-
Fitting the Simulated MIMIC Data With R Code – OpenMx, lavaan, sem Fitting the Simulated MIMIC Data With R Code – OpenMx, lavaan, sem
-
-
Author Note Author Note
-
References References
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
15 Structural Equation Models
Get accessJohn J. McArdle, Department of Psychology, University of Southern California, Los Angeles, CA
Kelly M. Kadlec, Department of Psychology, University of Southern California, Los Angeles, CA
-
Published:01 October 2013
Cite
Abstract
The purpose of this chapter is to present an accessible overview of recent research on what are termed structural equation models (SEM). This presentation is intended for graduate level students in the behavioral sciences, possibly taking a SEM class, but formal algebra or calculus is not required. First, SEM is broadly defined, and the increasing use of this approach to data analysis is described. In general, SEM techniques are increasingly used in the behavioral and social sciences. Second, some technical features of SEM are presented to illustrate key benefits of SEM. Some classical issues are described that highlight issues SEM researchers usually find to be important, and the big appeal of SEM comes when if offers some hope to deal with these issues. Third, we consider the inclusion of common factors as latent variables in path models that can be incorporated into SEM. We claim that the inclusion of common factors is what really makes SEM different than other statistical approaches. Fourth, we describe how SEM calculation works, and this gives rise to various indices of goodness-of-fit. Many researchers herald these techniques, although this seems to be a leftover from prior statistical training. Fifth, we provide an illustration of contemporary data generation and computer programming (using CALIS, Mplus, and OpenMx). In the final section, we illustrate some options from our previous SEM work, answer specific questions about SEM practices, and include a discussion of issues for future SEM uses.
Sign in
Personal account
- Sign in with email/username & password
- Get email alerts
- Save searches
- Purchase content
- Activate your purchase/trial code
- Add your ORCID iD
Purchase
Our books are available by subscription or purchase to libraries and institutions.
Purchasing informationMonth: | Total Views: |
---|---|
November 2022 | 6 |
December 2022 | 6 |
January 2023 | 2 |
February 2023 | 2 |
March 2023 | 6 |
April 2023 | 3 |
June 2023 | 2 |
August 2023 | 8 |
September 2023 | 1 |
October 2023 | 7 |
November 2023 | 2 |
December 2023 | 1 |
January 2024 | 2 |
April 2024 | 17 |
May 2024 | 7 |
June 2024 | 5 |
July 2024 | 4 |
August 2024 | 2 |
September 2024 | 5 |
October 2024 | 6 |
November 2024 | 7 |
December 2024 | 7 |
January 2025 | 7 |
February 2025 | 5 |
April 2025 | 1 |
Get help with access
Institutional access
Access to content on Oxford Academic is often provided through institutional subscriptions and purchases. If you are a member of an institution with an active account, you may be able to access content in one of the following ways:
IP based access
Typically, access is provided across an institutional network to a range of IP addresses. This authentication occurs automatically, and it is not possible to sign out of an IP authenticated account.
Sign in through your institution
Choose this option to get remote access when outside your institution. Shibboleth/Open Athens technology is used to provide single sign-on between your institution’s website and Oxford Academic.
If your institution is not listed or you cannot sign in to your institution’s website, please contact your librarian or administrator.
Sign in with a library card
Enter your library card number to sign in. If you cannot sign in, please contact your librarian.
Society Members
Society member access to a journal is achieved in one of the following ways:
Sign in through society site
Many societies offer single sign-on between the society website and Oxford Academic. If you see ‘Sign in through society site’ in the sign in pane within a journal:
If you do not have a society account or have forgotten your username or password, please contact your society.
Sign in using a personal account
Some societies use Oxford Academic personal accounts to provide access to their members. See below.
Personal account
A personal account can be used to get email alerts, save searches, purchase content, and activate subscriptions.
Some societies use Oxford Academic personal accounts to provide access to their members.
Viewing your signed in accounts
Click the account icon in the top right to:
Signed in but can't access content
Oxford Academic is home to a wide variety of products. The institutional subscription may not cover the content that you are trying to access. If you believe you should have access to that content, please contact your librarian.
Institutional account management
For librarians and administrators, your personal account also provides access to institutional account management. Here you will find options to view and activate subscriptions, manage institutional settings and access options, access usage statistics, and more.