A Permutation Approach to Split-Plot Experiments

Abstract

Split-plot design may be refer to a common experimental setting where a particular type of restricted randomization has occurred during a planned experiment. The aim of this article is to suggest a new method to perform inference on split-plot experiments by combination-based permutation tests. This novel nonparametric approach has been studied and validated using a Monte Carlo simulation study where we compared it with the parametric and nonparametric procedures proposed in the literature. Results suggest that in each experimental situation where normality is hard to justify and especially when errors have heavy-tailed distribution, the proposed nonparametric procedure can be considered as a valid solution.

Keywords:

• Nonparametric combination
• Permutation tests
• Synchronized permutations

Mathematics Subject Classification:

• Primary 62K15
• Secondary 62G10

Acknowledgments

Authors wish to thank the University of Padova (CPDA 088513/08 and CPDA092350/09) and the Italian Ministry for University and Research (2008WKHJPK/002) for providing the financial support for this research.