Advenced linear models

lstat2210  2018-2019  Louvain-la-Neuve

Advenced linear models
4 credits
15.0 h + 5.0 h
Q1
Teacher(s)
Bertrand Aurélie (compensates Legrand Catherine); Legrand Catherine;
Language
French
Main themes
- Review of generalised linear models - Dispersion models - Linear mixed models. - Generalised linear mixed models. - Autoregressive models. - Marginal models and generalised estimating equations.
Aims

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.

 

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Content
- Review of generalised linear models - Dispersion models - Linear mixed models. - Generalised linear mixed models. - Autoregressive models. - Marginal models and generalised estimating equations.
Bibliography
Transparents du cours disponible sur Moodle.
Références données au cours.
Faculty or entity
LSBA


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

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Statistic: Biostatistics

Master [120] in Biomedical Engineering

Master [120] in Statistic: General

Master [120] in data Science: Statistic