Teacher(s)

Draye Xavier coordinator; El Ghouch Anouar; Govaerts Bernadette;

Language

French

Prerequisites

Introduction to probability and statistics (typ. courses LBIR1203 and LBIR1204)

Main themes

Quantitative data analysis methods in bioengineering ' Variance analysis with one and more classification factors, crossed or nested ' Generalised linear models (classification and regression factors) ' Random effect and mixed models ' Least square and maximum likelihood methods ' Analysis of categorical datas

Content

Table of content
Introduction
Models for a quantitative response and one fixed factor
'        Linear model with one quantitative factor
'        Polynomial and non linear model
'        Variance analysis with one fixed factor
Linear models for one quantitative response and two fixed factors
'        Variance analysis with two crossed fixed factors
'        Multiple linear regression
'        Covariancer analysis and general linear model
Variance components models
'        Variance analysis with one random factor
'        Estimation of random effects and variance components
Mixed linear models
'        Formulation of random effects and structure of the covariance matrix
'        Analysis of common mixed models in biology (genetics, experimental design)
'        Analysis of longitudinal data
'        Covariance analysis in mixed models
Models for categorical data (not included in LBIRA2101A)
'        Contingency tables
'        Logistic regression
'        Generalised linear models

Teaching methods

Course in auditorium
Introduction course to data importation in SAS
Practical courses prepared by the students, with a test half way during the semester

Evaluation methods

Written exam with methodological questions and exercices méthodologiques, case studies, SAS code writing.  Allowed material: 20 pages summary (10 pages resto/verso).

Other information

This course can be given in English.

Online resources

Moodle

Bibliography

Faculty or entity

AGRO