16  Linear Models

This section introduces linear-model-based methods for testing differences among groups and understanding factor effects.

The core chapters are:

  1. Confidence intervals (planned)
  2. Simple linear regression
  3. Interpreting linear regressions
  4. T-tests
  5. ANOVA
  6. Understanding interactions
  7. Generalised linear models
  8. Interpreting GLMs
  9. Mixed effects models
  10. Generalised additive models
  11. Time series analysis

These pages have some introductions to commonly used linear models that test the response of a continuous dependent variable against one or more predictor variables that may be continuous or categorical. Note that these are only named as different techniques (e.g., regression vs ANOVA) due to common usage in the literature that you will encounter - they all involve the same linear modelling framework.

Scatterplot of log(plant height) against temperature (C) in green, with a red fitted regression line rising from left to right

Author: Alistair Poore

Year: 2016