Linear Mixed Models

We’re excited to announce our upcoming course on Linear Mixed Models!

Linear mixed models, also referred to as hierarchical models or multilevel models, are widely used in research, to deal with non-independent data. This may include longitudinal data, where subjects are repeatedly measured, or clustered data, where individuals within a subgroup may be more related to one another than to individuals from a different subgroup.

This course is designed for life science researchers seeking to enhance their statistical analysis toolkit with mixed-effects modeling approaches, through a combination of theoretical foundations and hands-on exercises. Additionally, applications on biomedical and genomic datasets will be showcased.

Course content:

The multiple linear regression model
Theoretical basis of the linear mixed model
Random intercept and random slope models
Real-world data analysis using linear mixed models

Prerequisites:

- R and Rstudio : Basics of reading in data, handling data frames and generating plots using the traditional functions
- Statistics : Familiarity with basic concepts of statistical inference, hypothesis testing, confidence intervals, p-values, …. Knowledge of simple linear regression is recommended, as it is only briefly touched upon in the introduction.

Practicalities:

Dates: 16 and 18 June 2025

Time: tentative: 9:30-16:30 (estimated)

Location: Campus Drie Eiken, building Q, room Q.003

Registration:

Registration is free, and restricted to researchers affiliated with the Faculty of FBD or BIOMINA (FBD, FWET and FGGW). If you still want to participate, just send us a mail and we'll see what's possible. We require a budget code as part of our no-show policy. Any absence not communicated on or before June 15th will result in a 50€ no-show fee from the given budget code.

Organisers:

Jesse Berwouts (StatUa)

Erik Fransen (fac. FBD)

Eline Turcksin (Biomina)

This course is a collaborative effort between the FBD faculty and the core facilities BIOMINA and StatUa.