A progressive shift alternative to evaluate nonparametric tests for skewed data

Marco Marozzi, J. Reiczigel

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

When the power of different nonparametric tests is evaluated by simulation, the alternative hypothesis should be carefully designed to ensure validity of the results in the specific research field. In the article, we propose a probit-based progressive shift alternative that is more realistic than the simple shift alternative for skewed non-negative data that occur in many research areas. Our motivation comes from parasitology. The progressive shift alternative is used to compare the power of six location-scale tests and seven commonly used location tests for several skewed theoretical and empirical parasite distributions. It is shown that location-scale tests are more powerful than location tests. Programs for applying the methods studied in the article are freely available for download.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalCommunications in Statistics: Simulation and Computation
DOIs
Publication statusAccepted/In press - Jan 22 2018

Fingerprint

Non-parametric test
Evaluate
Alternatives
Probit
Empirical Distribution
Non-negative
Simulation

Keywords

  • Bootstrap
  • Nonparametric tests
  • Parasitology
  • Permutation
  • Power
  • simulation

ASJC Scopus subject areas

  • Statistics and Probability
  • Modelling and Simulation

Cite this

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