Applied Statistics for Educational Researchers (DUH165)
This seminar course provides an introduction to the software programs Mplus and R, with a focus on latent variable modeling. We will cover topics such as confirmatory factor analysis and structural equation modeling, along with relevant psychometric theory. You will learn how to import, visualize, describe, and analyze real-world datasets, as well as how to conduct reproducible analyses using Mplus and appropriate R codes.
Course description for study year 2024-2025
Course code
DUH165
Version
1
Credits (ECTS)
5
Semester tution start
Spring
Number of semesters
1
Exam semester
Spring
Language of instruction
English
Content
Learning outcome
By completion of this course, the PhD candidate will have gained the following:
Knowledge
- of measurement theory
- a good understanding of multiple regression and factor analysis in SEM
- a good understanding of hierarchical structures in data, and how to address them in analysis
- a good understanding of SEM and LGC in complex survey data
Skills:
- running SEM and LGC analyses in Mplus
- preparing results of such analyses for publication
General competencies:
- being able to choose and apply the right analyses for the given design and data
developing advanced strategies for further research
Required prerequisite knowledge
Recommended prerequisites
Exam
Form of assessment | Weight | Duration | Marks | Aid |
---|---|---|---|---|
Paper | 1/1 | Passed / Not Passed |
Evaluation will be based on the active participation and analyses performed in group work, presented in a brief paper.Coursework requirements: Active participation in lectures and seminars at the workshop. Self-study. The students’ workload will be approximately 150 hours of work.
Coursework requirements
Course teacher(s)
Course coordinator:
Lene VestadCourse teacher:
Simona Carla Silvia CaravitaCourse teacher:
Njål FoldnesCourse teacher:
Thormod IdsøeStudy Program Director:
Hein BerdinesenCourse teacher:
Ulrich DettweilerCourse teacher:
Knud KnudsenMethod of work
In this week-long seminar, we will introduce confirmatory factor analysis (CFA) and structural equation modeling (SEM), as well as latent interaction effects and multilevel modeling work within the SEM framework. The seminar also demonstrates how Latent Growth Curve Modelling can be understood as an extension of SEM with intercepts and/or slopes being modeled as latent variables, first as an unconditional latent curve model. We will then look at conditional Latent Growth Curve models (including mediation models, and a comparison of (latent) groups with different approaches to testing measurement invariance. The latter will also be replicated and shown with an introduction to R.
The working format is a blending of lectures, group discussions, and hands-on analyses in Mplus/R.
Overlapping courses
Course | Reduction (SP) |
---|---|
Advanced Statistics for Educational Researchers: Analyzing Structural Equation Models and Latent Growth Curves w/ MPlus (DSP165_1) | 5 |