Introduction to mixed-effects models using R

[5 half days] - [English]

Does your data carry a complex structure that does not allow the use of traditional models ? Maybe do they feature random factors or repeated measures ? Time to switch to the mixed-effects models !

Mixed models are a family of models with both fixed and random effects. They make it possible to take into account the correlation between several observations, in particular the temporal aspect of the data.

Introduction to mixed-effects models using R [5 half days] - [starts on 19-05-2025 à 09:30] - [English] - [Louvain-la-Neuve]

Training aims

Prerequisites
By registering for this training, you commit to a level of knowledge equivalent to the following training(s):

Content

• Simple structures :
  
  • Models with a random intercept
  • Models with a random intercept and a random slope

• More specific structure of variance-covariance matrix useful for longitudinal or spatial data
• Hierachical structures with more than 2 levels

Rate
This training course is recognized by the IABE, enabling participants to earn CPD points.
(Note that this is true for all SMCS courses.)

Methods and method families discussed
Mixed models
   Linear mixed model