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A Trinomial Test for Paired Data When There are Many Ties

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  • Guorui Bian
  • Michael McAleer

    ()
    (University of Canterbury)

  • Wing-Keung Wong

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.

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File URL: http://www.econ.canterbury.ac.nz/RePEc/cbt/econwp/1020.pdf
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Bibliographic Info

Paper provided by University of Canterbury, Department of Economics and Finance in its series Working Papers in Economics with number 10/20.

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Length: 18 pages
Date of creation: 06 May 2010
Date of revision:
Handle: RePEc:cbt:econwp:10/20

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Keywords: Sign test; trinomial test; non-parametric test; ties; test statistics; hypothesis testing;

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  1. Hansen, B.E., 1991. "Inference when a Nuisance Parameter is Not Identified Under the Null Hypothesis," RCER Working Papers 296, University of Rochester - Center for Economic Research (RCER).
  2. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
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