Statistical tests for the comparison of two samples: the general alternative

Markus Neuhaeuser*, Anke Welz, Graeme D. Ruxton

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


It is common to test the null hypothesis that two samples were drawn from identical distributions; and the Smirnov (sometimes called Kolmogorov-Smirnov) test is conventionally applied. We present simulation results to compare the performance of this test with three recently introduced alternatives. We consider both continuous and discrete data. We show that the alternative methods preserve type I error at the nominal level as well as the Smirnov test but offer superior power. We argue for the routine replacement of the Smirnov test with the modified Baumgartner test according to Murakami (2006), or with the test proposed by Zhang (2006).

Original languageEnglish
Pages (from-to)903-909
Number of pages7
JournalCommunications in Statistics: Simulation and Computation
Issue number2
Early online date10 Feb 2015
Publication statusPublished - 2017


  • Nonparametric statistics
  • Rank tests
  • Smirnov test


Dive into the research topics of 'Statistical tests for the comparison of two samples: the general alternative'. Together they form a unique fingerprint.

Cite this