Introduction to Statistical Modelling

  1. Introduction

  2. One-Way Analysis of Variance (ANOVA) Recap

  3. Two-Way ANOVA - Assessing Two Effects in Same Model

  4. Two-Way ANOVA - Allowing for Structure in The Data

  5. Paired T-Test Using Two-Way ANOVA & ANOVA With More Effects

  6. Regression Recap

  7. General Linear Models (GLMs) - Introduction

  8. GLM Fitting Categorical & Continuous Effects

  9. Using GLMs to Adjust for Confounding Variables & Using GLMS for Prediction

  10. GLMS – general points

  11. GLMS – checking model assumptions

  12. GLMs - General Points

  13. Models for Other Data Types

  14. Logistic Regression

  15. Logistic Regression Example – Assessing Risk Factors

  16. Logistic Regression Example Continued – Predicting Risk

  17. Logistic Regression – General Points

  18. Ordinal Logistic Regression

  19. Survival Analysis

  20. Repeated Measures Data

  21. Mixed (or Multilevel) Models

  22. Choice of Software Package

  23. Self-Learning Resources

Keywords: Statistical modelling, Roslin Institute

Difficulty level: Beginner

Licence: Other (Not Open)

Authors: Helen Brown

Introduction to Statistical Modelling Training session with Dr Helen Brown, Senior Statistician, at The Roslin Institute, December 2015. 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. Statistical modelling, Roslin Institute