Introduction to Mixed Models

  1. Introduction

  2. What Are Mixed Models?

  3. Potential Advantages of Mixed Models

  4. Historical Perspective

  5. Example 1: Biological & Technical Replicates

  6. Example 2: Rabbit Inspiration Time – Sources of Variation

  7. Non-Normal Data

  8. Example 3: Non-normal data

  9. Trials Involving Comparisons Between Units

  10. Example 4: Crossover Trial

  11. Repeated Measures Data

  12. Practical considerations – Negative Variance Components

  13. Significance Testing for Fixed Effects

  14. Model Assumptions & Model Checking Methods

  15. Sample Size Estimation

  16. Explaining A Mixed Model

  17. Statistical Packages

Keywords: Mixed models, Roslin Institute

Difficulty level: Beginner

Licence: Other (Not Open)

Authors: Helen Brown

Introduction to Mixed Models Training session with Dr Helen Brown, Senior Statistician, at The Roslin Institute, March 2016. These training sessions were given to staff and research students at the Roslin Institute. The material is also used for the Animal Biosciences MSc course taught at the Institute. Mixed models, Roslin Institute