Course Unit Title:
MAN 606 – Multivariate Data Analysis
Semester
Spring
Lecture
Department:
Management and Organizations PhD Program
Instruction Methods
(Hours)
Recitation Project /
Homework Other Total
Field Study
45
75
45
135
ECTS
Credit
10
300
Language
Compulsory/Elective
Prerequisites
Course Description
English
Compulsory
None
This course involves advanced multivariate data analysis methods that are in
widespread use in management and organization studies.
Course Objectives
This course aims at equipping students with applied knowledge of several
methods of multivariate analysis.
Students who complete this course will be able to
1. Choose between different methods of multivariate data analysis based on
their needs and characteristics of their data
2. Assess validity and reliability of the scales they use
3. Conduct inferential multivariate statistical analyses that are in widespread
use in management and organization studies
4. Evaluate the advantages and limitations associated with the analysis
methods they use.
Learning Outcomes
Required Textbook
and Additional
Resources
The course is based on multiple resources. The resources that will be used
each week are indicated in the program.
Frequency
Contribution to Overall
Grade (%)
1
1
1
30
40
30
Assessment Methods
Midterm
Final examination
Report
As this is an applied course, attendance is compulsory. Students who miss
more than two classes will fail.
Plagiarism and other ethical issues:
Students are expected to learn about plagiarism and observe ethical codes.
Failure to observe codes of ethical conduct will be punished. For example, any
attempt at plagiarism (the partial or complete use of other people’s work as
one’s own) will result in a failing grade and disciplinary action. To learn more
about plagiarism now, please consult:
http://www.plagiarism.org
Lecturer
Associate Professor Çetin ÖNDER
COURSE CONTENT
Week
Topic
1
Validity and reliability
2
3
4
Exploratory factor analysis
(EFA)
Structural Equations
Modeling: Core constructs,
methods and tools
Measurement model and
confirmatory factor analysis
(CFA)
Readings
Hair, J.F., Anderson, R.E., Tatham, R.L., Black,
W.C. (1998) Multivariate Data Analysis, 5th Edition,
Prentice Hall, Upper Saddle River, New Jersey, Ch.
3, “Factor Analysis”, p. 87-138.
Hair, J.F., Anderson, R.E., Tatham, R.L., Black,
W.C. (1998) Multivariate Data Analysis, 5th Edition,
Prentice Hall, Upper Saddle River, New Jersey, Ch.
11, “Structural Equation Modeling”, p. 577-666.
MacCallum, R.C., Austin, J.T. (2000) Applications
of structural equation modeling in psychological
research, Annual Review of Psychology, 51: 201226.
Byrne, B.M. (2001) Structural Equation Modeling
With AMOS : Basic Concepts, Applications, and
Programming. Mahwah, NJ: Lawrence Erlbaum.
[Application 1: “Testing for the Factorial Validity of
a Theoretical Construct (First-Order CFA Model)”, p.
57-97]
Noar, S.M. (2003) The role of structural equation
modeling in scale development, Structural Equation
Modeling, 10(4): 622-647.
5
6
Measurement model and
confirmatory factor analysis
(CFA)
Multi-group CFA and
measurement invariance
Edwards, J.R. (2001) Multidimensional constructs in
organizational behavior research: An integrative
analytical framework, Organizational Research
Methods, 4 (2): 144-192.
Vandenberg, R.J., Lance, C.E. (2000) A review and
synthesis of the measurement invariance literature:
Suggestions, practices, and recommendations for
organizational research. Organizational Research
Methods, 3: 4-69.
Byrne, B.M. (2004) Testing for multigroup
invariance using AMOS graphics: A road less
traveled, Structural Equation Modeling, 11(2): 272300.
Byrne, B.M. (2001), Application 4, “Testing for the
Validity of a Causal Structure”, p. 142-172.
7
Path analysis: Direct and
mediated effects
8
Multi-group path analysis
9
Midterm
Hunt, S.D., Morgan, R.M. (1994) Organizational
commitment: One of many commitments or key
mediating construct? Academy of Management
Journal, 37(6): 1568-1587.
Byrne, B.M. (2001) Application 8: “Testing for
Invariant Pattern of Causal Structure”, p. 247-266.
Hair, J.F., Anderson, R.E., Tatham, R.L., Black,
W.C. (1998) Multivariate Data Analysis, 5th Edition,
Prentice Hall, Upper Saddle River, New Jersey, Ch.
4, “Multiple Regression Analysis”, p. 141-216.
10
11
12
Multivariate regression
analysis
Discriminant analysis and
logistic regression
Multivariate analysis of
variance (MANOVA)
Wasti, S.A. (2003) Organizational commitment,
turnover intentions and the influence of cultural
values. Journal of Occupational and Organizational
Psychology, 76: 303-321.
Hair, J.F., Anderson, R.E., Tatham, R.L., Black,
W.C. (1998) Multivariate Data Analysis, 5th Edition,
Prentice Hall, Upper Saddle River, New Jersey, Ch.
5, “Multiple Discriminant Analysis and Logistic
Regression”, p. 239-325.
Hair, J.F., Anderson, R.E., Tatham, R.L., Black,
W.C. (1998) Multivariate Data Analysis, 5th Edition,
Prentice Hall, Upper Saddle River, New Jersey, Ch.
6, “Multivariate Analysis of Variance”, p. 326-386.
Hair, J.F., Anderson, R.E., Tatham, R.L., Black,
W.C. (1998) Multivariate Data Analysis, 5th Edition,
Prentice Hall, Upper Saddle River, New Jersey, Ch.
9, “Cluster Analysis”, p. 469-568.
13
Cluster analysis
14
Analysis support session for
your reports
15
Presentations
Wasti, S.A. (2005) Commitment profiles:
Combinations of organizational commitment forms
and job outcomes. Journal of Vocational Behavior,
67: 290-308.