Biostatistics with R An Introductory Guide for Field Biologists

This chapter handles more advanced types of ANOVA models, those that contain multiple explanatory variables (factors). We start with the hierarchical ANOVA, illustrated by two example studies, and we describe how the variation of the response variable is decomposed, introducing the concept of variance components. We set apart and discuss the properties of the split-plot ANOVA model and we illustrate its use by evaluating the results of a field experiment. Finally, we discuss the repeated measurements ANOVA, which is a very important model for analysing both monitoring data and data from manipulative experiments. Although it is typically analysed using a type of a split-plot ANOVA, the repeated measurements ANOVA model has further assumptions that are discussed in the text. The methods described in this chapter are accompanied by a carefully-explained guide to the R code needed for their use, including the nlme, lme4, effects, and car packages.