2023-2024 / PSYC5899-1

Complex statistical models and software use


30h Th, 30h Pr

Number of credits

 Master in psychology (120 ECTS)6 crédits 


Francis Pérée

Language(s) of instruction

French language

Organisation and examination

Teaching in the first semester, review in January


Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The formulation of increasingly complex theories in the field of social sciences as well as the quantitive analysis of data based on these theories are facilitated at this moment, on the one hand, thanks to sophisticated methods of statistical analysis and, on the other hand, to the existence of specific and adequate statistical softwares. In this context, Structural Equation Modeling (SEM) primarily makes it possible to confirm the validity of theories concerning complex situations, among others those characterized by the presence of latent or unobserved variables. These methods are also known under other names such as "causal modeling" and "analysis of covariance structures".

Learning outcomes of the learning unit

The principal objective of the course is to familiarize the students with the basic concepts and procedures used in the specification, identification, valuation and adjustment of structural models. These concepts are illustrated by using concrete examples. The course will enable the students to use the "Lavaan" package of software R for Windows and Mac, while minimizing the use of the matrix algebra that is normally used for this type of modelling.

Prerequisite knowledge and skills

To have a basic knowledge of statistics. The knowledge of the concepts of linear regression and factor analysis is an additional asset. To be familiar with the use of a statistical software.

Planned learning activities and teaching methods

The course is organized in the form of theoretical seminars and practical workshops. Exercises are proposed within the framework of those classes and are solved by individual work on a computer.

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face course

Additional information:

Each course session will be delivered in person in the CAFEIM room (B32). It will be completed by exercises to be carried out in session, exercises whose patch will be provided and by additional exercises online (eCampus).

In addition, the free R software and the "Lavaan" package allow each student to have them on his personal computer.

Recommended or required readings

Pérée F.P., Analyse confirmatoire des modèles à variables latentes (Analysis of covariance models), Use of R software (package Lavaan), Syllabus of course, University of Liege Editions, january 2022

Exam(s) in session

Any session

- In-person

written exam ( open-ended questions )

Additional information:

The evalution takes place at the end of the academic year. The evaluation is carried out by means of a three-hour writtent test in wich each student has to solve on his osn, on a computer, several concrete problems in the application of statistics.

The students may use their course book, personal notes and examples of programs.

Work placement(s)

Organisational remarks and main changes to the course


UNIVERSITY OF LIEGE Service of Quantitative Psychology Sart Tilman B32 Quartier AGORA Place des Orateurs, 2 B-4000 Liège BELGIUM Tél : +32 4 366 22 31 e-mail : fperee@uliege.be

Association of one or more MOOCs