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Two-sample inference based on one-sample ranked set sample sign statistics 

Author: Oumlmer Oumlztuumlrk a
Affiliation:   a Department of Statistics, The Ohio State University, Marion, Ohio
DOI: 10.1080/10485259908832760
Publication Frequency: 8 issues per year
Published in: journal Journal of Nonparametric Statistics, Volume 10, Issue 2 1999 , pages 197 - 212
Formats available: PDF (English)
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Abstract

A two-sample sign test is developed for ranked set samples. It is shown that the testing procedure is distribution free but requires evaluation of the incomplete beta function. Efficiency and type I error, in general, depend on the measured observations and the ratio of cycle sizes. It is shown that there is a substantial gain in the efficiency of the test even when there are ranking errors. On the other hand, the type I error is inflated for imperfect ranking. The proposed test is superior to the two-sample Mann-Whitney-Wilcoxon ranked set sample test when the underlying probability model has heavy and long tail distribution, and the number of quantified observations in each cycle is small. We provide a simple way to implement the procedure.
Keywords: Confidence interval; efficiency; nonparametric test; distribution free
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