Course Syllabus
MKT 6355 – Research Methods II
Fall 2001
Instructor: Dr. Dennis B. Arnett
Office: BA 705
Phone: 742-2951
E-mail: darnett@ba.ttu.edu
Prerequisite: Advanced graduate standing and MKT 5355 or consent of instructor.
Note: All statements in this syllabus are tentative and, therefore, subject to change. The student
is responsible for staying informed of all changes.
Course Description: An in-depth examination of measurement issues, including latent
constructs and data-gathering procedures in marketing.
Objectives: The course is designed for students who need a significant familiarity with those
statistical analysis techniques known as “structural equation modeling.” The primary objectives
of this class are to give students the ability to: (1) recognize the instances when these techniques
may be useful in research, (2) ability to understand the limitations of these techniques, and (3)
use these techniques in their own research programs.
Grading: The student’s course grade will be calculated as follows:
First Examination
Second Examination
Class Participation
Individual Project
20%
20%
20%
40%
Individual Project: Using your own dataset (or one that you begged, borrowed, or stole)
develop and test a model. You must use LISREL for your analysis. Once the analysis is
complete write up your results (i.e., the methods section of a paper). Use the style of a major
journal in your area that normally publishes articles that use SEM techniques.
Suggested Resources:
Books
Bollen, Ken (1989), Structural Equation Modeling with Latent Variables, New York: John
Wiley and Sons.
Loehlin, J.C. (1992), Latent Variable Models: An Introduction to Factor, Path, and Structural
Analysis (2nd Edition), Hillsdale, NJ: Earlbaum Associates.
Schumacker, Randall E. and Richard G. Lomax (1996), A Beginner’s Guide to Structural
Equation Modeling, Mahwah, NJ: Earlbaum Associates.
Websites
David Kenny’s site (http://nw3.nai.net/%7Edakenny/causalm.htm)
Ed Rigdon’s site (http://www.gsu.edu/~mkteer/semfaq.html)
Wynne Chin’s site (http://disc-nt.cba.uh.edu/chin/indx.html)
Student Software
LISREL (Student Edition) (http://www.ssicentral.com/other/entry.htm)
PLS Path (Version 3.01) (available from me)
Tentative Class Topics
August 28th … Topic 1: Introduction to class
Assigned readings for next class:
Meehl, Paul E. (1990), “Why Summaries of Research on Psychological Theories are often
Uninterpretable,” Psychological Reports, 66(1), 367-375.
(Students will be responsible for presenting their understanding of assigned points in the article.)
Hunt, Shelby D. (1991), Modern Marketing Theory, Cincinnati, OH: South-Western Publishing
Co., pp. 78-89.
Topic 2: (A) What do we mean when we say that we are testing a theory? (B) Do “good”
theories explain, predict, or do both?
Assigned readings for next topic:
LISREL notation cheat sheet (from me)
Chapter 3 in Schumacker, Randall E. and Richard G. Lomax (1996), A Beginner’s Guide to
Structural Equation Modeling, Mahwah, NJ: Earlbaum Associates.
Rigdon, Edward E. (1998), “Structural Equation Modeling,” in Modern Methods for Business
Research, George A. Marcoulides (ed.), Mahwah, NJ: Earlbaum Associates, pp. 251-294.
Topic 3: (A) Regression? Path Analysis? Exploratory factor analysis? Confirmatory factor
analysis? Structural equation modeling? (B) Measurement models versus structural models. (C)
Introduction to LISREL notation.
Assigned readings for next topic:
Gerbing, David W. and James C. Anderson (1988), “An Updated Paradigm for Scale
Development Incorporating Unidimensionality and Its Assessment,” Journal of
Marketing Research, 25(May), 186-192.
Bollen, Kenneth and Richard Kennox (1991), “Conventional Wisdom on Measurement: A
Structural Equation Perspective,” Psychological Bulletin, 110(2), 305-314.
Topic 4: Measurement issues. (A) How do we model formative and reflective measures in
SEM? (B) Validity. (C) Reliability.
Assigned readings for next topic:
Anderson, James C. and David W. Gerbing (1988), “Structural Equation Modeling in Practice: A
Review and Recommended Two-Step Approach,” Psychological Bulletin, 103(3), 411423.
LISREL sample output (from me)
Topic 5: (A) What is covariance structure analysis? (B) What does it do to my data? (C) What
are all those numbers coming out of LISREL? (D) LISREL syntax.
Assigned readings for next topic:
Data (from me)
Topic 6: (A) So, this is a measurement model! (B) Is it a “good” one? (C) Can we make it
better?
Assigned readings for next topic:
None. Study for test.
Topic 7: Test! (Tentatively October 9th)
Assigned readings for next topic:
Review Anderson and Gerbing (1988) again.
Topic 8: (A) Convergent validity? (B) Discriminant validity? (C) So, the measurement model
fits the data. What next? (B) Predictive validity?
Assigned readings for next topic:
Schumacker, Randall E. and Richard G. Lomax (1996), A Beginner’s Guide to Structural
Equation Modeling, Mahwah, NJ: Earlbaum Associates, pp. 119-129
Topic 9: (A) Why are there so many fit indexes? (B) Which one(s) should I use? (C) Can we
use other methods of estimation besides ML?
Assigned readings for next topic:
Schumacker, Randall E. and Richard G. Lomax (1996), A Beginner’s Guide to Structural
Equation Modeling, Mahwah, NJ: Earlbaum Associates, pp. 25-27.
Chin, Wynne W. and Peter A. Todd (1995), “On the Use, Usefulness, and Ease of Structural
Equation Modeling in MIS Research: A Note of Caution,” MIS Quarterly, June, 237-246.
Topic 10: (A) Why isn’t LISREL working? It keeps telling me that the phi matrix is nonpositive
definite. (B) How big of a sample should I have? (C) What do you mean it’s not
converging? I spent 6 months collecting this data. Now what?
Assigned readings for next topic:
Sellin, Norbert (1995), “Partial Least Squares Modeling in Research on Educational
Achievement,” in Reflections on Educational Achievement Papers in Honor of Neville
Postlethwaite, Wilfried Bos and Rainer H. Lehmann (eds.), Munich: Waxmann
Publishing Co., pp. 256-266.
Sellin, Norbert and J. P Keeves (1998), “Path Analysis and Latent Variables,” in Educational
Research, Methodology, and Measurement: An International Handbook, J. P. Keeves
(ed), New York: Pergamon Press.
PLSPath output (from me)
Topic 11: (A) PLS, what’s that? (B) Hey, where are the fit indices? (C) Does it fit or not?
Assigned readings for next topic:
Data.
Topic 12: Discuss PLS runs.
Assigned readings for next topic:
Fornell, Claes and Fed L. Bookstein (1982), “Two Structural Equation Models: LISREL and
PLS Applied to Consumer Exit-Voice Theory,” Journal of Marketing Research,” 19,
440-452.
Cassel, Claes, Peter Hackl, and Anders H. Westlund (1999), “Robustness of Partial LeastSquares Method for Estimating Latent Variable Quality Structures,” Journal of Applied
Statistics, 26(4), 435-446.
Topic 13: When should I use a program, such as LISREL, and when should I use PLS?
Topic 14: Test!! (Tentatively December 4th)
Supplementary Readings
Edwards, Jeffrey R. and Richard P. Bagozzi (2000), “On the Nature and Direction of
Relationships Between Constructs and Measures,” Psychological Methods, 5(2), 155174.
Bollen, Kenneth A. and R. Lennox (1991), “Conventional Wisdom on Measurement: A
Structural Equation Perspective,” Psychological Bulletin, 110, 305-314.