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 journalJournal articlepeer-review

    17 Citations (Scopus)
    23 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
    Early online date7 Dec 2010
    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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