Identifying Latent Data Structures: Structural Equation Modelling I


Structural equation modeling (SEM) is a general statistical modeling technique to study the relationships among observed variables. It spans a wide range of multivariate methods including path analysis, mediation analysis, confirmatory factor analysis, growth curve modeling, and many more. Many applications of SEM can be found in the social, economic, behavioral and health sciences, but the technology is increasingly used in disciplines like biology, neuroscience and operation research. SEM is often used to test theories or hypotheses that can be represented by a path diagram. In a path diagram, observed variables are depicted by boxes, while latent variables (hypothetical constructs measured by multiple indicators) are depicted by circles. Hypothesized (possibly causal) effects among these variables are represented by single-headed arrows. If you had ever found yourself drawing a path diagram in order to get a better overview of the complex interrelations among some key variables in your data, this course is for you.

This course is part of a larger course series in Data Analysis consisting of 19 individual modules. Find more information and enroll for this module via

The first day of the course provides an introduction to the theory and application of structural equation modeling. On the second day, we discuss several special topics that are often needed by applied users (handling missing data, nonnormal data, categorical data, longitudinal data, etc.). Hands-on sessions are included in order to ensure that all participants are able to perform the analyses using SEM software. The software used in this course is the open-source R package `lavaan' (see

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Identifying Latent Data Structures: Structural Equation Modelling I

  • Type of course: This is an on campus course.
  • Dates & times: February 7 & 8, 2022, from 9 am to 12 pm and from 1 pm to 4 pm
  • Venue: Faculty of Psychology and Educational Sciences, Campus Dunant, PC-lokaal 1.2 - Dunant 2, 9000 Gent
  • Target audience: This course targets everyone with an interest in testing theories or models that involve relationships between both observed and latent variables. The audience for this course can include both novices with little or no previous experience with SEM, as well as existing users who wish to refresh or update their theoretical and practical understanding of structural equation modeling.
  • Exam/certificate: Participants who attend all classes receive a certificate of attendance via e-mail at the end of the course. Additionally, participants who follow both Part I and Part II of this course can, if they wish, take part in an exam. Upon succeeding in this test a certificate from Ghent University will be issued. The exam consists of a take home project assignment. Students are required to write a report by a set deadline.
  • Course prerequisites: Participants should have a solid understanding of regression analysis and basic statistics (hypothesis testing, p-values, etc.) at a level equivalent of Module 2 'Drawing Conclusions from Data: an Introduction' of this year's program. Some knowledge of exploratory factor analysis (or PCA) is recommended, but not required. Because lavaan is an R package, some experience with R consistent with the course content of Module 1 'Getting Started with R Software for Data Analysis' (reading in a dataset, fitting a regression model) is recommended, but not required.
  • Funding: => Our academy is recognised as a service provider for the 'KMO-portefeuille'. In this way small and middle sized businesses located in the Flanders region can save up to 30% on the registration fee for our courses. You can request this subsidy via up until 14 calender days after the course has started. => UGent PhD students can apply for a full refund from their Doctoral School.
  • Reduction: => If two or more employees from the same company enrol simultaneously for this course a reduction of 20% on the module price is taken into account starting from the second enrolment => Reduced prices apply to coworkers in governmental institutions, non-profit organisations and higher eduction as well as for students and the unemployed.
  • Enrolling for this course is possible via the IPVW-ICES website.