A trinomial test for paired data when there are many ties

Guorui Bian, Michael McAleer, Wing Keung WONG*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
5 Downloads (Pure)


This paper develops a new test, the trinomial test, for pairwise ordinal data samples to improve the power of the sign test by modifying its treatment of zero differences between observations, thereby increasing the use of sample information. Simulations demonstrate the power superiority of the proposed trinomial test statistic over the sign test in small samples in the presence of tie observations. We also show that the proposed trinomial test has substantially higher power than the sign test in large samples and also in the presence of tie observations, as the sign test ignores information from observations resulting in ties.

Original languageEnglish
Pages (from-to)1153-1160
Number of pages8
JournalMathematics and Computers in Simulation
Issue number6
Publication statusPublished - Feb 2011

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)
  • Numerical Analysis
  • Modelling and Simulation
  • Applied Mathematics

User-Defined Keywords

  • Non-parametric test
  • Sign test
  • Test statistics
  • Ties
  • Trinomial test


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