Mixed Models for Biologists: A practical crash course

Mixed models are a powerful, flexible tool that empower biologists to control for various sources of non-independence ("pseudoreplication”) without losing (hardly any) statistical power to detect a significant pattern in their variable of interest. In this three-day course, students, who must already be familiar with linear models and GLMs in R, will learn how to code and implement the next natural step: mixed models. Students will learn the difference between fixed effects and random effects, will learn how to ditch clunky transformations and instead embrace the native distribution of the data, and will be forced to think critically about experimental design. Students will also analyze their own data, so this course is particularly well suited to those with data in hand (datasets will also be provided for those without their own data). This course is practical, hands on and workshop style with very little mathematics per se. 

9:45-10 Intros & Icebreaker

Lecture: Overview of Linear Models

Lecture: Overview of GLMs

Lecture: Distributions

Lunch

PM: practical examples and working through GLM code

Lecture - overview of mixed models

11:00 Coffee Break 

11:15 - 11:45 Q & A session as needed

11:45 - 12:30 Work though First GLMM example

12:30 - 13:00 Q & A on distributions and misc. topics

LUNCH - 1 hour

Go through annotated code

14:00-15:15 Seed example + Q & A

15:15 15 min Break

15:30-16:30 - Hunting example + Q & A

16:30 5 min break

16:35-17:00 Count data example + Q & A

9:45-10:30 Group discussion: Student example one

10:30-11:00 Group discussion: Student example two 

define questions and set up global models on whiteboard

11:00 Coffee Break

11:15 - 13:00 Break out groups of three students: define questions & construct global models on paper

LUNCH - 1 hour

14:00-14:30 Short lecture: Additional considerations when modelling

14:30-15:15 Students work through their own data themselves

15:15 15 min Break

15:30-16:45 Students work through their own data themselves

16:45-17:00 Closing remarks and final questions (if necessary)

3 days - 18 hours - Schedule: ~09:30 - 12:30 & 14:00 - 17:00

Coordination

Luke L. Powell | BIOPOLIS-CIBIO

Instructor (s)
Luke L. Powell | BIOPOLIS-CIBIO

Pan Nikolaou | BIOPOLIS-CIBIO
Joaquim Faria | BIOPOLIS-CIBIO

The course will be open to a maximum number of 20 participants. 

75% of available student slots are reserved for BIODIV students.

 Priority will be given to:

• 1st year and other PhD students attending the BIODIV Doctoral Program;

• PhD students attending other courses;

• Other post-graduate students and researchers.

(A minimum number of participants is required for the course to take place)
• This is a genuinely advanced statistics course, so students MUST be familiar with linear modelling (comfortable) and GLMs (at least a good working knowledge). If you do not have this background, we kindly ask that you refrain from applying, as the material will be very challenging and may prevent others with the appropriate preparation from taking part. Feel free to email the course coordinator if you are not sure if your background is appropriate.

Deadline:  10 October 2025

To apply fill the FORM
A copy of your submitted form will be sent to the email address you provided. This email is your confirmation that the application was successfully submitted.

If you don't receive this email, your application was not successfully submitted.

We will email you the results within 10 working days after the application deadline.