Introduction to Structural Equation Modeling (SEM) (25-29 November 2013) POSTPONED. New dates have not been settled yet


Faculty 

Professor Bo Bernhard Nielsen & Professor Sabina Nielsen

Course coordinator 
Prerequisites 

Prerequisite
PhD enrollment – open to all faculty and practitioners

Prerequisite/progression of the course
The course requires basic understanding of statistics, but does not require knowledge of structural equation modeling or any particular SEM software.
 

Aim 

This course is designed to help participants understand the theoretical basis and practical application of structural equation modeling. More specifically, we will address the following issues:

1.  What is structural equation modeling and what types of research questions can it help answer?
2. Theoretical understanding of measurement models and structural models.  
3. Conducting basic SEM analysis.
4. Reading SEM output and providing guidelines for reporting SEM results.
5. Analysis of interaction effects with continuous and categorical variables.
6. Latent growth modeling and overview of more advanced analyses.

The course is a combination of theory and lab sessions using MPLUS software.
 

Content 

Day 1: Foundations (9:30-15:30)

9:30-10:00      Introduction
10:00-11:00     Basic concepts
11:00-11:15     Coffee break
11:15-12:00     Introduction to SEM  
12:00-13:00     Lunch break
13:00-14:15     Introduction to MPLUS
14:15-14:30     Bio break
14:30-15:30     Steps of SEM

Day 2: Measurement models I (9:30-15:30)

9:30-11:00       Specification & identification of measurement models
11:00-11:15     Coffee break
11:15-12:00     Estimation of measurement models
12:00-13:00     Lunch break
13:00-14:15     Re-specification of measurement models
14:14-14:30     Bio break
14:30-15:30     Discuss your own research

Day 3: Measurement models II (9:30-15:30)

9:30-10:00      Discuss your own research
10:00-11:00     Construct and discriminant validity
11:00-11:15     Coffee break
11:15-12:00     Measurement models in practice
12:00-13:00     Lunch break
13:00-14:15     Multiple group analysis I
14:15-14:30     Bio break
14:30-15:30     Second order factors & formative measurement

Day 4: Structural Models (9:30-15:30)

9:30-10:00      Discuss your research
10:00-11:00     Structural models I
11:00-11:15     Coffee break
11:15-12:00     Structural models II
12:00-13:00     Lunch break
13:00-14:15     Structural models in practice
14:15-14:30     Bio break
14:30-15:30     Discuss your research

Day 5: Advanced Modeling and Reporting (9:30-15:30)

9:30-10:00      Discuss your research
10:00-11:00     Interaction effects
11:00-11:15     Coffee break
11:15-12:00     Multiple group analysis II
12:00-13:00     Lunch break
13:00-14:15     Reporting
13:30-13:45     Bio break
13:45-15:15     Wrap-up & evaluations
 

Teaching style 

Lectures and interactive lab-sessions

Exam 

Course certificates will be issued based on participation

Course literature 

Main text:
Rex B. Kline (2010). Principles and practices of structural equation modeling, 3d edition, New York: Guilford Press.

Articles:
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182.  
McCallum, R. C., Roznowski M. & Necowitz L.B. (1992). Model modifications in covariance structure analysis: the problem of capitalization on chance. Psychological Bulletin. 111:490–504.
 

PhD School 
PhD School in Economics and Management
Department 
Department of Strategic Management and Globalization

COURSE SPECIFICATIONS

PhD School
Doctoral Schoool of Economics and Management

Department
Department of Strategic Management and Globalization

Level
PhD

ECTS
5

Language
English

Location
TBA

Fee
DKK 6.500

Maximum number of participants
24

Enrol no later than
1 October 2013

Registration
Please fill in the application form and send it by e-mail to Lone Petersen

course_application_form.pdf

Contact PhD Administration
Lone Petersen lp.research@cbs.dk