CIRJE-F-662 "A Trinomial Test for Paired Data When There are Many Ties"
Author Name Bian, Guorui, Michael McAleer and Wing-Keung Wong
Date September 2009
Full Paper PDF file
Remarks Subsequently published in Mathematics and Computers in Simulation Volume 81, Issue 6, February 2011, Pages 1153–1160.
Abstract

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 diRerences between observations, thereby increasing the use of sample information. Simulations demonstrate the power superiority of the proposed trinomial test statis- tic 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.