Course Name: Measurement and Factor Analysis.
Time: From 21st to 23rd April 2026 (3 full days).
Place: University of Jyväskylä, Agora Building, Mattilanniemi 2, 40100 Jyväskylä.
Credits: 5-8 ECTS.
The course offers flexible credit options based on the components completed:
• 5 ECTS: Core components (pre-exam, mandatory interactive videos, posting to course forum, mandatory written assignment, in-person workshop, and mandatory data analysis assignment).
• +1 ECTS: Additional written assignment (to be completed before the in-person workshop).
• +1 ECTS: Additional data analysis assignment (to be completed after the in-person workshop, course instructors tutor and provide feedback over Zoom).
• +1 ECTS: Additional video lectures (to be completed after the in-person workshop).
Learning Goal and Objectives:
This course aims to provide doctoral students with both theoretical understanding and practical skills in measurement development and factor analysis for research applications. The course addresses common measurement challenges faced by researchers across disciplines. By the end of the course, students will be able to:
1) Understand fundamental measurement theories and their implications for research design.
2) Differentiate between reflective and formative measurement approaches.
3) Apply exploratory and confirmatory factor analysis techniques appropriately.
4) Evaluate measurement reliability beyond basic Cronbach’s alpha.
5) Assess different forms of validity (convergent, discriminant, nomological).
6) Identify and address common method variance issues to a degree that they are addressable.
7) Diagnose and resolve problems with non-convergent measurement models.
8) Test for measurement invariance across groups.
9) Address complex measurement challenges in research contexts.
10) Critically evaluate published measurement instruments using contemporary standards.
11) Leverage large language models to assist with statistical software applications.
Instruction and Examination:
The course has pre-workshop online components, a three-day intensive in-person workshop, and post-workshop assignments. The pre-workshop component includes readings, interactive video lectures (https://youtu.be/dxxwUeFtNyk), online forum discussions, and a written assignment. A pre-exam using the examination system at participating universities must be completed before the workshop. The online components of the course run on JYU Moodle.
Each in-person workshop day runs from 9:15 to 17:00 and combines theoretical instruction with practical hands-on application using computers provided by JYU or the participants’ laptops, with approximately half the time dedicated to each. The workshop includes:
• Interactive lectures on key theoretical concepts.
• Guided hands-on exercises using statistical software.
• Small group discussions and collaborative problem-solving.
• Practical demonstrations of measurement development and validation.
• Integration of large language models to assist with statistical software applications.
A course dinner will be arranged on the second evening to facilitate networking and informal discussion.
The in-person workshop follows this general structure:
Day 1: Measurement Theory and Foundations
• Introduction to measurement theory and applications.
• Reliability concepts and assessment techniques.
• Validity frameworks and evaluation.
• Hands-on application with statistical software.
• Group exercises applying measurement concepts.
Day 2: Exploratory and Confirmatory Factor Analysis
• Exploratory factor analysis principles and techniques.
• Factor extraction and rotation methods.
• Confirmatory factor analysis: Model specification.
• Modification indices and their interpretation.
• Hands-on application with statistical software.
Day 3: Advanced Measurement Topics
• Model diagnostics and troubleshooting.
• Common method variance: Detection and control.
• Measurement invariance testing.
• Advanced measurement models (including bi-factor models).
• Introduction to formative measurement concepts.
• Integration with broader confirmatory factor analysis models.
Additional credit components:
• Optional pre-workshop written assignment on philosophical foundations of measurement.
• Optional post-workshop advanced data analysis assignment.
• Optional additional video lectures on advanced measurement topics.
The course supports multiple statistical software packages, including R, Stata, jamovi, Mplus, and SPSS. Students wishing to use MPlus will need to have their own licenses. While all software options are supported for mandatory components, R and Stata are preferred, and additional exercises for extra credit are available only for these software packages.
Grading: 1-5
The assessment will be based on:
• Pre-exam on foundational concepts (10%).
• Pre-workshop written assignment: Critical review of measurement approaches in published research (20%).
• Active participation during the workshop (30%).
• Post-workshop data analysis assignment: Application of factor analysis techniques to a dataset (40%).
Admittance: Registration link: https://forms.gle/fuQnPMEUiTG2ozsD9
A Maximum of 25 students will be admitted to the course. Applications should include 1) a CV and 2) a brief description (max. 300 words) of the students’ research interests and why they want to participate in the course. The application deadline is February 15th, 2026. Accepted students will be notified by February 21st. Accepted applicants will then access the Moodle page and course material and can register for the pre-exam.
Instructors:
Dr. Mikko Rönkkö is an Associate Professor of Entrepreneurship at Jyväskylä University School of Business and Economics (JSBE) and a docent at Aalto University School of Science. He has published extensively on research methods in both methodology journals and applied journals in management and information systems. Dr. Rönkkö serves as an Associate Editor for Organizational Research Methods and is on the editorial board of Entrepreneurship Theory and Practice. He runs a research method-focused YouTube channel with over 10,000 subscribers and maintains expertise in statistical methods, research design, and entrepreneurship.
Dr. Reza Yamini is a Postdoctoral Researcher at Jyväskylä University School of Business and Economics (JSBE) who recently completed his doctoral studies. His research focuses on quantitative research methods in entrepreneurship with a particular interest in structural equation models.
Course Coordinator and Contact Information: Reza Yamini, reza.r.yamini@jyu.fi, University of Jyväskylä (JSBE).