Essex Summer School in
Social Science Data Analysis

Raymond Sin-Kwok Wong

Raymond Sin-Kwok Wong is a Professor of the Division of Social Science at the Hong Kong University of Science and Technology. His substantive research interests include social stratification and mobility, sociology of education, economic development, and comparative sociology. He has taught SEM seminars regularly at the Division of Social Science at HKUST and Department of Sociology at University of California-Santa Barbara.

0D Introduction to Structural Equation Modeling

Raymond Sin-Kwok Wong, Hong Kong University of Science and Technology
17 -28 June (two week course / 35 hrs)

Course Content

This course focuses on sociological (and other social-scientific) applications of path analysis and structural equation models. Following a review of basic ideas about the structure, interpretation, estimation, and inference in recursive causal models, the course will work through problems of specification and identification in latent-variable models and non-recursive models, using published examples where possible. The LISREL model will be introduced and its use in the specification of a variety of models will be reviewed. They include: factor models, MIMIC models, recursive and non-recursive models (with and without latent variables), multiple group models (with or without latent mean structures), models of repeated measurement, models with missing data, the specification of latent structural models for ordinal data, and latent growth curve modeling.

Course Objectives

The course objectives are to make students comfortable with the terminology, logic, and use of the SEM framework. Of course, understanding the “language” of SEM will also allow them to keep up with the latest developments. By the end of the course, students will not only understand and appreciate SEM modeling, but they will also have proficiency in a wide variety of social science applications.

REQUIRED TEXTBOOKS

Bollen, Kenneth. 1989. Structural Equation Modeling with Latent Variables. New York: Wiley.

Byrne, Barbara M. 1998. Structural Equation Modeling with LISREL, PRELIS, and SIMPLIS: Basic Concepts, Applications, and Programming. Mahwah, NJ: Lawrence Erlbaum Associates.

Jöreskog, Karl and Dag Sörbom. 1996. LISREL 8: User's Reference Guide. Chicago, IL: Scientific Software International.

Kline, Rex. 2010. Principles and Practice of Structural Equation Modeling. Third Edition. New York: Guilford.

TENTATIVE SCHEDULE

Day 1 Review: Matrix Algebra and Multiple Regression

Day 2 Introduction to Structural Equation Models

Day 3 Recursive Models

Day 4 Confirmatory Factor Analysis

Day 5 Models with Unobservables and MIMIC Models

Day 6 Modeling and Testing Strategies

Day 7 Non-Recursive Models

Day 8 Multiple-Group LISREL Models

Day 9 Models for Ordinal Data

Day 10 Latent Growth Curve Modeling

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