Department of Economics
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.
Mathematics and Computers in Simulation
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Sign test, Trinomial test, Non-parametric test, Ties, Test statistics
Bian, Guorui, Michael McAleer, and Wing Keung Wong. "A trinomial test for paired data when there are many ties." Mathematics and Computers in Simulation 81.6 (2011): 1153-1160.