Introduction to Structural Equation Modeling

Dr. Randall E. Schumacker

Aim of Course:

Structural Equation Modeling (SEM) is a general statistical modeling technique to establish relationships among variables. A key feature of SEM is that observed variables are understood to represent a small number of "latent constructs" that cannot be directly measured, only inferred from the observed measured variables. This course covers the theory of SEM, and includes practical work with computer software and real data. It covers the key concepts in SEM - at the conclusion of the course students will be able to specify different forms of models, using observed, latent, dependent and independent variables. Student will be able to conduct confirmatory factor analysis, and diagram SEM models.

Who Should Take This Course:

Market researchers, educational researchers, sociologists and psychologists, political scientists, economists, and survey researchers.

For those enrolled in a Program of Advanced Statistical Studies, this is a required or elective course in the following Programs:

• Statistics for Social Sciences - elective

Course Program:

The course is structured as follows:

The Instructor:

Dr. Randall E. Schumacker is Professor in Educational Research at the University of Alabama. He is the co-author of A Beginner's Guide to Structural Equation Modeling (with Richard Lomax), Advanced Structural Equation Modeling: New Developments and Techniques (with George Marcoulides) and the co-editor (with George Marcolides) of Advanced Structural Equation Modeling: Issues and Techniques and Interaction and Nonlinear Effects in Structural Equation Modeling. Dr. Schumacker was the founder, editor (1994-1998), and is the current emeritus editor of Structural Equation Modeling: A Multidisciplinary Journal. He also founded the Structural Equation Modeling Special Interest Group at the American Educational Research Association.

Organization of the Course:

The course takes place over the Internet, at statistics.com. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor. The course is scheduled to take place over 4 weeks, and typically requires 5-15 hours per week (read more). At the beginning of each week, participants receive the relevant material, in addition to answers to exercises from the previous session. During the week, participants are expected to go over the course materials and work through exercises. Discussion among participants is encouraged. The instructor will provide answers and comments.

Credit:

Academic credit (2.0 graduate semester hours) for this course is available via the American Council on Education (ACE) Credit Recommendation Service. Click here for details. This course also offers continuing education units (CEU's). For those successfully completing the course (generally this means marks of 50% or better on the homework), 5.0 CEU's and a certificate will be issued by statistics.com, upon request.

Dates:

Nov. 12 - Dec. 10, 2010
Click here to be notified of future course offerings.

Participants gain access to the online materials on the first day of the course, and typically spend about 15 hours per week (at their convenience). You retain full access to course materials, including discussion board, for two weeks after the course closing date.

Level:

Intermediate

Prerequisite:

You should be familiar and comfortable with the concepts in Basic Concepts in Probability and Statistics, Introduction to Statistics 1: Inference for a Single Variable, and Introduction to Statistics 2: Working with Bivariate Data. Some prior work with modeling is also helpful - statistics.com courses that are useful in this respect include Introduction to Regression, Introduction to Datamining, and Logistic Regression. If you are not familiar with the basics of educational measurement and assessment, or would like a refresher, please also consider taking "Introduction to Assessment/Measurement in Education" .

Course Text:

The course text is A Beginner's Guide to Structural Equation Modeling, 3rd edition, published April 2010, by Randall E. Schumacker and Richard Lomax. You can order this text by clicking here.

Software:

The course will provide illustrations in LISREL, a programming environment. You can download a free student version of LISREL from the textbook website. The Introductory guide and user's manual are also available here. TA's can provide LISREL support if needed.

Registration:

Register Online - $499
Register Online (academic) - $399 (you must be affiliated with a college, university or high school)

Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.

Note: Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.

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