EPSY 651                    STRUCTURAL EQUATION MODELING   SPRING 2008

MONDAYS  7- 9:25

 

Instructor: Dr. Victor Willson, Professor of Educational Psychology                    Tel: 979-845-1808

email: v-willson@tamu.edu        Office: 718B Harrington:

Office hours M 3-5, TR 2-3:30, or by appt.            979-696-0193 (H)

 

TOPICS COVERED:

            Theory of covariance structures             Testing structural equations models

            Measurement models                                        Factor analysis models  Path models                                          General linear model applications

 

Course orientation: projects are planned, analyzed, and written up for each general topic based on meaningful

data, either the students or large data bases supplied by the instructor. Grading is based on the written

product. Students will be expected to bring in readings related to their interest area each week for

discussion based on recent volumes of Structural Equation Modeling.

 

Computer background: Students should be familiar with either SPSS or SAS; we will use AMOS and Mplus 3 as analysis engines; LISREL, SAS, and EQS are also available for use. Students can select their preference for work. Each student will receive a semester-long ID and password to the College of Education and Human Development server to access the computer programs.

Statistics background: Students should have one-two semesters of statistics, such as EPSY 640-641 or STAT 651-652. The course is not a theory course per se, and will not be a proof-oriented course, but focuses

instead on model assumptions, model building, revision, and linkage to subject matter theory. More advanced students can still benefit since there is a wealth of theoretical material in the readings.

Text:     Kline, R. Principles and Practice of Structural Equation Modeling, Second Edition. ·  The Guilford Press; 2 edition (2004)

·  ISBN-10: 1572306904

·  ISBN-13: 978-1572306905

TOPICS:                                                                     READINGS*             PROJECT

 

JAN 14            Intro to Course, Demonstration of

                        computer programs

 

JAN 21            Theory of Covariance Structures           Kline 1-3                     

                        Intro to AMOS                        

 

JAN 28            Data preparation; Path Analysis Kline 4-5                     

                        Intro EQS

 

FEB 4  Advanced Path Modeling and   Kline 6                         Project 1 due

                        Regression ; Intro to LISREL

 

FEB 11            Measurement Models                           Kline 7                         Project 2 due

                        Intro to MPLUS 3

 

FEB 18            Confirmatory Factor Analysis                Kline 7

                       

 

FEB 25            Extensions- MTMM, Hierarchical         Kline 7                         Project 3 due

                        Factor Analysis                        

 

MAR 3            Latent Structure Models                       Kline 8

 

MAR 17          Nonrecursive Models                           Kline 9                         Project 4 due

 

MAR 24                     Means & Multilevel Models      Kline 10          

 

MAR 31          Latent Growth Curve Modeling             Kline 10                       Project 5 due

                         And Time Series Analysis                    

 

APR21, 28       Student Project Presentations

 

MAY 9             Project final report papers due in APA or other format

 

Grading:

 Each Project will require a computation and interpretive report or analysis based on either AMOS, PROC CALIS of SAS, LISREL, EQS, or LISREL. Data may be provided by the student or can be selected from one of the research data sets available from the instructor. Each Project will be graded as 100 points; late submissions will be docked 10 points per week late. Student Presentation will be given 100 points. Final paper will be graded up to 400 points and submission is required for passing the course. Papers not completed by deadline can be submitted later with course grade I given until submitted.

100-90: A

80-89:  B

70-79:  C

below 70: F

 

Reading list:  Required text: Kline, R. B. (2005). Principles and Practices of Structural Equation Modeling, 2nd Ed. NY: Guilford.

*Articles will be handed out on most topics in class at least 1 week in advance

 

Students with Special Needs

   The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for persons with disabilities.  Among other things, this legislation requires that allstudents with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities.  If you believe you have a disability requiring an accommodation, please contact the Office of Support Services for Students with Disabilities in Room 126 of the Student Services Building.  The telephone number is 845-1637.

      Any student who could require assistance in the event of a necessary evacuation of the building in which this class is taught are asked to notify the instructor so that individuals can be identified to assist him/her during an evacuation.

 

 

Handouts

   The handouts used in this course are copyrighted. By "handouts" I mean all materials generated for this class, which include but are not limited to syllabi, quizzes, lab problems, in-class materials, review sheets, and additional problem sets. Because these materials are copyrighted, you do not have the right to copy the handouts, unless I expressly grant permission.

 

Academic Dishonesty

Academic Integrity Statement: An Aggie does not lie, cheat, or steal or tolerate those who do.

   As commonly defined, plagiarism consists of passing off as one’s own ideas, words, writings, etc. which belong to another. In accordance with this definition, you are committing plagiarism if you copy the work of another person and turn it in as your own, even if you should have the permission of that person. Plagiarism is one of the worst academic sins, for the plagiarist destroys the trust among colleagues, without which research cannot be safely communicated.

   If you have any questions regarding plagiarism, please consult the Honor Council Rules and Procedures on the web at http://www.tamu.edu/aggiehonor