From nonparametric tests to mixed models: A brief overview of statistical tools frequently used in comparative psychology

In this chapter, I provide an overview of some of the statistical tools commonly used in comparative psychology (namely, nonparametric and parametric tests) and also of the methods and approaches I foresee becoming increasingly popular in comparative psychology. I begin with treatments of nonparametric tests, analysis of variance (ANOVA), and regression, and I then explain how ANOVA and regression relate to the general linear model and can be expanded to the GLM and mixed models. Throughout, I mention assumptions of these procedures and point out issues about their use as well as design and data limitations they impose. Subsequently, I treat more generic issues, such as the concept of interactions, effect sizes, and confidence intervals, and also briefly touch on model selection and more general issues related to statistical inference