DRE 7049 Longitudinal Structural Equation Modeling

DRE 7049 Longitudinal Structural Equation Modeling

Course code: 
DRE 7049
Department: 
Economics
Credits: 
3
Course coordinator: 
Ulf Henning Olsson
Course name in Norwegian: 
Longitudinal Structural Equation Modeling
Product category: 
PhD
Portfolio: 
PhD Economics courses
Semester: 
2022 Autumn
Active status: 
Active
Level of study: 
PhD
Teaching language: 
English
Course type: 
One semester
Introduction

This course gives an introduction to longitudinal structural equation modeling: The longitudinal CFA Model, Longitudinal Panels Models, Multiple Group Models, Mediation and Moderation. Basic understanding of confirmatory factor analysis (CFA) and structural equation modeling (SEM) is recommended. Students are given hands-on experience by working with data, using descriptive statistics to motivate models, and using models to turn data into actionable knowledge. The course will focus on “learning by doing”. R/lavaan is the preferred software.   

Learning outcomes - Knowledge

After completing the course, the students should be able to understand the concept of analyzing multivariate longitudinal data and have an understanding of the link between classical SEM and Longitudinal SEM. In addition, the students will have knowledge on how modern software can be used to analyze big and complex data matrices, and at the next level turn the results in to meaningful mathematical models.  

Learning outcomes - Skills

Upon completion of this course, the student should be able to analyze multivariate longitudinal  data, and apply suitable statistical techniques for exploratory as well as confirmatory analysis, use modern software and be able to understand and interpret the results. A central learning outcome is to be able to write and communicate the results in a scientific manner.

General Competence

Longitudinal modeling is a broad area, based on mathematics, statistics and methodology.  Being a mathematical tool, there are of course assumptions that are not always met in a real world setting. After completing the course students should be aware of these limitations, and be able to reflect upon how this can influence the final results in a research project, which is an encompassing goal of the course.  

Course content
  • Introduction
    • Some basic covariance algebra
    • Model fit, sample size and power
    • Measurement levels
  • Longitudinal Confirmatory factor analysis
    • Configural invariance
    • Weak invariance
    • Strong invariance
    • Multiple Group Models
  • Longitudinal Panel Models
    • Basics of a panel model
    • The Basic Simplex Change Process
    • Building of a panel model
    • Mediation and Moderation
Teaching and learning activities

Lectures and exercises

R/lavaan (and/or Mplus)

Software tools
Software defined under the section "Teaching and learning activities".
R
Qualifications

Enrollment in a PhD Programme is a general requirement for participation in PhD courses at BI Norwegian Business School.
External candidates are kindly asked to attach confirmation of enrollment in a PhD programme when signing up for a course. Other candidates may be allowed to sit in on courses by approval of the courseleader. Sitting in on a course does not permit registration for the course, handing in exams or gaining credits for the course. Course certificates or confirmation letters will not be issued for sitting in on courses.

Disclaimer

Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Assessments
Assessments
Exam category: 
Submission
Form of assessment: 
Written submission
Weight: 
100
Grouping: 
Individual
Duration: 
1 Month(s)
Comment: 
Termpaper
Exam code: 
DRE 70491
Grading scale: 
Pass/fail
Resit: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
18 Hour(s)
Student's own work with learning resources
32 Hour(s)
Prepare for teaching
10 Hour(s)
Examination
20 Hour(s)
Sum workload: 
80

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 3 ECTS credit corresponds to a workload of at least 80 hours.