A Trinomial Test for Paired Data When There are Many Ties

Guorui Bian, Michael McAleer and Wing-Keung Wong

Working Papers in Economics from University of Canterbury, Department of Economics and Finance

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 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.

Keywords: Sign test; trinomial test; non-parametric test; ties; test statistics; hypothesis testing (search for similar items in EconPapers)
JEL-codes: C12 C14 C15 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2010-05-06
New Economics Papers: this item is included in nep-ecm
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Downloads: (external link)
https://repec.canterbury.ac.nz/cbt/econwp/1020.pdf (application/pdf)

Related works:
Journal Article: A trinomial test for paired data when there are many ties (2011)
Working Paper: A Trinomial Test for Paired Data When There are Many Ties (2010)
Working Paper: A Trinomial Test for Paired Data When There are Many Ties (2010)
Working Paper: A Trinomial Test for Paired Data When There are Many Ties (2010)
Working Paper: A Trinomial Test for Paired Data When There are Many Ties (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:cbt:econwp:10/20

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