Mixed linear models

lstat2210  2022-2023  Louvain-la-Neuve

Mixed linear models
4.00 credits
15.0 h + 7.5 h
Q1
Teacher(s)
Language
French
Prerequisites
Concepts and tools equivalent to those taught in teaching units
LSTAT2020Logiciels et programmation statistique de base
LSTAT2120Linear models
LSTAT2100Modèles linéaires généralisés et données discrêtes
Main themes
- Review of generalised linear models - Dispersion models - Linear mixed models. - Generalised linear mixed models. - Autoregressive models. - Marginal models and generalised estimating equations.
Learning outcomes

At the end of this learning unit, the student is able to :

1 This is a second cycle course giving a critical overview of recent scientific developments in the field. It will deal with present extensions of linear and generalised linear models. The considered extensions will be of two types : - a explicit modelling of dispersion as a function of available covariates. - a amendment of (generalised) linear models to deal with clustered or longitudinal data.
 
Bibliography
Transparents du cours disponible sur Moodle.
Références données au cours.
Teaching materials
  • transparents sur moodle
Faculty or entity


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Data Science : Statistic

Master [120] in Biomedical Engineering

Master [120] in Statistics: Biostatistics

Master [120] in Statistics: General

Certificat d'université : Statistique et science des données (15/30 crédits)