Abstract

The paper explores a testing problem which involves four hypotheses, that is, based on observations of two random variables X and Y, we wish to discriminate between four possibilities: identical survival functions, stochastic dominance of X over Y, stochastic dominance of Y over X, or crossing survival functions. Four-decision testing procedures for repeated measurements data are proposed. The tests are based on a permutation approach and do not rely on distributional assumptions. One-sided versions of the Cramer-von Mises, Anderson-Darling, and Kolmogorov-Smirnov statistics are utilized. The consistency of the tests is proven. A simulation study shows good power properties and control of false-detection errors. The suggested tests are applied to data from a psychophysical experiment.

Keywords

Stochastic dominance; Repeated measurement; Four-hypothesis test; Permutation test; Nonparametric approach

Published in

AStA Advances in Statistical Analysis
2023, Volume: 107, number: 3, pages: 443-467
Publisher: SPRINGER

SLU Authors

• Ekström, Magnus

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    
  • Umeå University

UKÄ Subject classification

Probability Theory and Statistics


Publication identifier

DOI: https://doi.org/10.1007/s10182-022-00446-8

Permanent link to this page (URI)

https://res.slu.se/id/publ/117259