Within‐Case Designs: Distribution‐Free Methods

Abstract

In within‐case designs, individuals are measured repeatedly over time or across multiple experimental conditions. Univariate and multivariate parametric procedures for testing within‐case effects may lose statistical power under departures from a multivariate normal distribution. Nonparametric procedures based on rank scores or bootstrapping are useful alternatives for testing within‐case effects when the data are skewed or have heavy tails. We consider these methods when there are missing observations and for complex designs.