Course
Applied Statistics for Educational Researchers (DUH165)
Facts
Course code DUH165
Credits (ECTS) 5
Semester tution start Spring
Language of instruction English
Number of semesters 1
Exam semester Spring
Time table View course schedule
Literature Search for literature in Leganto
Introduction
This seminar course offers a practical and theory-based introduction to psychometric measurement theory, with a focus on tools and techniques essential for conducting high-quality research in psychology and related fields. Throughout the course, we will explore key topics such as confirmatory factor analysis (CFA) and structural equation modeling (SEM), alongside foundational psychometric concepts.
Participants will gain hands-on experience working with real-world datasets and learning how to import, visualize, describe, and analyze data using contemporary statistical software. The course emphasizes not only technical proficiency but also critical thinking about measurement validity, reliability, and model fit, which are central to robust scientific inquiry.
Content
Learning outcome
By the end of this course, PhD candidates will have acquired the following knowledge, skills and competencies:
Knowledge
- An understanding of basic psychometric measurement theory.
- A solid grasp of multiple regression and factor analysis within the structural equation modeling (SEM) framework.
- A good understanding of SEM and latent growth curve (LGC) models in the context of complex survey data.
Skills
- Conducting preliminary analyses to assess the validity and reliability of data.
- Performing SEM and LGC analyses.
- Preparing the results of these analyses for publication.
General Competencies:
- Ability to choose and apply the appropriate analyses for the given design and data.
- Development of advanced strategies for future quantitative research.
Required prerequisite knowledge
Recommended prerequisites
Exam
Fakta
Weight 1/1
Marks Passed / Not Passed
Evaluation will be based on a brief individual paper. The paper should contain a short thematic conceptualization, research questions, a section presenting sample and procedure, analytic strategies, and results, and be no longer than 4000 words +/-10% (references excluded).
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
80 % attendance
At least 80 % attendance in lectures and seminars.
Method of work
In this week-long seminar, we will introduce confirmatory factor analysis (CFA) structural equation modeling (SEM), 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, an
The working format is a blending of lectures, group discussions, and hands-on analyses.
Overlapping courses
| Course | Reduction (SP) |
|---|---|
| Advanced Statistics for Educational Researchers: Analyzing Structural Equation Models and Latent Growth Curves w/ MPlus (DSP165_1) , Applied Statistics for Educational Researchers (DUH165_1) | 5 |