rankFD: An R Software Package for Nonparametric Analysis of General Factorial Designs

Many experiments can be modeled by a factorial design which allows statistical analysis of main factors and their interactions. A plethora of parametric inference procedures have been developed, for instance based on normality and additivity of the effects. However, often, it is not reasonable to assume a parametric model, or even normality, and effects may not be expressed well in terms of location shifts. In these situations, the use of a fully nonparametric model may be advisable. Nevertheless, until very recently, the straightforward application of nonparametric methods in complex designs has been hampered by the lack of a comprehensive R package. This gap has now been closed by the novel R-package [rankFD](https://CRAN.R-project.org/package=rankFD) that implements current state of the art nonparametric ranking methods for the analysis of factorial designs. In this paper, we describe its use, along with detailed interpretations of the results.