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Structural equation models, fall 2014


Kimmo Vehkalahti, University Lecturer, Adj.Prof., D.Soc.Sci (Statistics)
Fellow of the Teacher's Academy

Target group

This is an application-oriented basic course of Structural Equation Models (SEM) using Mplus software.

  • It is primarily targeted to Doctoral students of Social Sciences, who have no prior knowledge of SEM.
  • The course is also suitable for Master's students of Statistics (e.g., Social Statistics, Psychometrics).
  • The number of participants is limited to maximum of 20.

Before the course you should have fairly good practical skills of Factor Analysis and Regression Analysis.
See the pre-course materials below!

No Mplus skills will be needed before the course, as we will start from the very beginning. Unfortunately, Mplus is available in the computer class only (unless you buy it). All the analyses of this course may also be computed using R, LISREL or other SEM software, but it requires independent work (we will focus exclusively on Mplus).

Text book

We will closely follow a text book by Barbaba M. Byrne, and learn its most central topics through empirical examples.

  • We begin by going (fast) through the chapters 1 and 2 (first week).
  • The primary focus will then be on the chapters 3, 4, 6, 7 and 9 (basically, one week for each).
  • The chapters 5 and 8 will serve for optional assignments (see below).
  • (The chapters 10-12 will be excluded.)


Please buy the book ASAP (you may well consider the e-book!). It may be quite difficult to follow the course without it.


The course is scheduled this time on period II, starting in the end of October and ending before Xmas.

It is essential to participate on the lectures and the computer classes. Both will begin immediately on 28th of October.

  • Lectures on Tuesdays 8-10 and Wednesdays at 12-14 (Unioninkatu 37, 2nd floor, seminar room 4).
    • Note: Starting from 12th of November the Wednesday lectures are in Unioninkatu 40, lecture room 12.
  • Computer class on Tuesdays at 10-12 (Snellmaninkatu 12, IT classroom 110).

The last lecture of the course will be on 10th of December.

The classes on 9th of December will be cancelled, as I will be in a conference in Pisa, Italy.


There is no exam, as this is learning by doing and practicing. Credits will be earned as follows (more details during the course):

  • 6 cu: active participation, weekly assignment reports (based on chapters 3,4,6,7,9)
  • 8 cu: all of the above plus an additional report (based on chapter 5 or chapter 8 or perhaps own data)

Grading will be based on the active participation as well as the quantity and quality of the assignment reports.

Moodle will be used for sharing the materials, your reports etc. with all other students of the course.

Pre-course material

  1. Introduction to SEM by KV
    • Keynote talk given in the Annual Seminar of FiDPEL:
      The Finnish Doctoral Programme in Education and Learning (2013)
    • Suitable stuff for everyone interested in this course
  2. Multivariate linear relations by prof. Theodore W. Anderson (Stanford University, USA)
  3. Matrices of SEM

    • Learn the basics of Greek letters needed with SEM
    • Suitable stuff at least for students of Statistics
  4. Moodle forum example
    • Learn the basics of Greek mythology related to multivariate statistical analysis
    • Suitable stuff at least for students of Statistics

Praise for the course (16 Oct 2014)

Dear Kimmo,
during my ERASMUS semester in Helsinki I attended the first version
of your SEM course which, as I just read on your website, you still
offer. After attending it and after coming back to Munich and after
finishing my Master thesis I started to work at the Faculty of
Social Sciences here and I could even use the expertise gained from
your course directly in a paper which got published a while ago (it
is in German, though). Hence, I need to tell you, that you still
are my personal most-influental memory of my Finland semester.
Thanks for that :)
Best regards from Munich,
Mario Haim, M.A.
Institut für Kommunikationswissenschaft und Medienforschung
Ludwig-Maximilians-Universität München
Oettingenstr. 67 / Raum EU111
D-80538 München

(Quoted with permission.)

Register for the course

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