Linear modeling: Hands-on with Fixed and Mixed effects models

Objective

This course aims to introduce linear regression models with fixed and random effects. Regression model assumptions, diagnostics and model-building strategies are showed. Remedies for violated assumptions are explained. This course provides hands-on training with R software.

Course overview

1. Effects and statistical regression models

• define and classify…
  • effects
  • statistical regression models
  • linear regression models.

2. Linear models with only fixed effects

• develop, check and fit the following regression models in R:
  • One-way analysis of variance (ANOVA)
  • Two-way ANOVA without interaction
  • Two-way ANOVA with interaction
  • Linear regression models
  • Multivariable regression models with fixed effects.
• develop and identify ‘reference’ statistical models in R.

3. Linear mixed-effects models

• develop, check and fit linear mixed-effects regression models in R.
• tumour growth curve analysis is used as pivotal application of linear mixed-effects regression models in preclinical cancer research.

Prerequisites

This course assumes basic knowledge of statistics and use of R , which would be obtained from our Introductory Statistics Course and an “Introduction to R for Solving Biological Problems” run at the Genetics department (or equivalent).

• Introduction to Solving Biological Problems with R
• Introduction to Statistical Analysis

Format

• Presentation with slides
• Demonstrations
• Practicals

Timetable

Day	Start	End	Subject
21st February 2025	9.00 am	10.00 am	Effects and regression models
	10.00 am	11.00 am	Analysis of variance (ANOVA)
	11.00 am	12.00 am	Linear regression
	12.00 am	13.00 am	Multivariable linear regression models (only fixed effects)
28th February 2025	9.00 am	10.00 am	Linear mixed-effects models
	10.00 am	13.00 am	Tumour growth curve analysis

Materials

• Effects and regression models
  • Slides PDF
  • Tutorial HTML
  • Tutorial R Markdown
• Analysis of variance (ANOVA)
  • Slides PDF
  • Tutorial HTML
  • Tutorial R Markdown
• Simple linear regression
  • Slides PDF
  • Tutorial HTML
  • Tutorial R Markdown
• Multiple linear regression models (only fixed effects)
  • Slides PDF
  • Tutorial HTML
  • Tutorial R Markdown
• Linear mixed-effects models
  • Slides PDF
• Tumour growth curve analysis in R
  • Tutorial HTML
  • Tutorial R Markdown

Course data

• Please Download this zip file to have all the datasets and R files used in this course.

System requirements

• Laptop and installed R.
• Please, install the following R packages before the course:
  • GLMsData
  • tidyverse
  • nlme
  • multcomp
  • lmtest

Your feedback

• After the course, please fill the feedback form you receive by email.

Going further

• Transforming data