Course detail

Welcome to Introduction to Structural Equation Modelling (2026)

Description: 

Research typically address topics such as “organizational culture”, “project success”, and “trust”. These concepts are latent variables or non-observable variables that cannot be directly measured with a single metric. Instead, they are indirectly measured using a set of indicators or manifest variables. Structural Equation Modelling (SEM) is one way to analyze such nonobservable variables and the relationships between them.

SEM is a very powerful tool in a variety of scenarios, such as: 
1. When the research goal is to predict key constructs or to identify key constructs.
2. When the researcher has complex models that comprise many different constructs, indicators, and relationships.
3. When the research model is evaluated with secondary or archival data.

Prerequisites:
Introduction to statistics (solid knowledge of multiple linear regressions).

Learning objectives:
The ultimate goal is to develop from a hypothesized theory a structural model and evaluate it based on the most recent assessment criteria.

Teaching methods:
Lectures, exercises, and individual case studies.

Criteria for assessment:
Written assignment of an individually developed SEM model

Lecturer: Daniel Russo, Associate Professor at the Department of Computer Science, AAU-Copenhagen

Short Bio: Daniel is using SEM (in both the Covariance-Based or Partial Least Squares modes) extensively in his research, in both cross-sectional and longitudinal fashion. Works, using SEM have been published in flagship journals of his research community, such as ACM Transactions on Software Engineering and Methodology, Empirical Software Engineering, and The Journal of Systems and Software. He also authored the methodological guidelines for pursuing and reporting SEM studies in Computer Science, published on ACM Computing Surveys. As an internationally recognised expert, he is regularly invited to provide opinion or commentary papers, such as for Communications for the Association for Information Systems.

Important information concerning PhD courses: 

There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course..

For external PhD students: This course is a general course and is prioritised for PhD Students enrolled at Aalborg University. If there are available seats, PhD students from other universities will be accepted. You will be notified shortly after the deadline if you have been accepted.

To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.

For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at phdcourses@adm.aau.dk  When contacting us please state the course title and course period. Thank you.