First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Psychology
Course unit
PSP7078617, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2018/19

Information on the course unit
Degree course Second cycle degree in
PS1087, Degree course structure A.Y. 2017/18, A.Y. 2018/19
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination LATENT VARIABLE MODELS
Department of reference Department of Philosophy, Sociology, Education and Applied Psychology
E-Learning website
Mandatory attendance No
Language of instruction Italian
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge EGIDIO ROBUSTO M-PSI/03

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses M-PSI/03 Psychometrics 6.0

Course unit organization
Period Second semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Lecture 6.0 42 108.0 No turn

Start of activities 25/02/2019
End of activities 14/06/2019
Show course schedule 2019/20 Reg.2017 course timetable

Examination board
Board From To Members of the board
3 2019/20 01/10/2019 30/11/2020 ROBUSTO EGIDIO (Presidente)
ANSELMI PASQUALE (Membro Effettivo)
STEFANUTTI LUCA (Membro Effettivo)
VIDOTTO GIULIO (Membro Effettivo)
2 2018/19 01/10/2018 30/11/2019 ROBUSTO EGIDIO (Presidente)
ANSELMI PASQUALE (Membro Effettivo)
STEFANUTTI LUCA (Membro Effettivo)
VIDOTTO GIULIO (Membro Effettivo)

Prerequisites: The knowledge derived from the other methodology courses.
Target skills and knowledge: This course provides an introduction to some advanced data analysis methods, with special emphasis on the latent trait and the latent class analysis. It also helps students develop the computational skills needed to carry out statistical procedures in practical settings.
Examination methods: Oral exam concerning the theoretical and applicative aspects dealt with during the lectures as well as the exercises performed.
Assessment criteria: The evaluation of the student’s preparation will be based on the level of understanding of the topics, the acquisition of concepts and methodologies treated and on his/her ability to apply them in an autonomous and aware manner.
Course unit contents: - Statistical and mathematical prerequirements and introduction to the latent variable concept
- Rasch models
- Log-linear models with latent variables
- Data analysis software
Planned learning activities and teaching methods: Besides the lectures, exercises on concrete analysis cases will be proposed in which the students, alone or in a group, will have the opportunity to test the concepts learned.
Additional notes about suggested reading: On the course's Moodle page will be made available to students the slides of the lectures, and any material used in class.
It is stressed that the availability of such material in no way can be considered a substitute of the lectures frequency, which remains the most effective way to approach the discipline.
Textbooks (and optional supplementary readings)
  • Cristante, Francesca; Mannarini, Stefania, Misurare in psicologia. Il modello di Rasch. Roma: Bari, Laterza, 2004. Cerca nel catalogo
  • Robusto, Egidio; Cristante, Francesca, Analisi delle classi latenti di variabili psicosociali. Modelli, metodi, applicazioni. Milano: LED, 2012. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Problem solving

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • One Note (digital ink)
  • Latex

Sustainable Development Goals (SDGs)
Quality Education