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Nonparametric tests for the median from a size-biased sample 

Authors: Qing Kang a; Paul I. Nelson b
Affiliations:   a Department of Statistics, North Dakota State University, Fargo, ND, USA
b Department of Statistics, Kansas State University, Manhattan, KS, USA
DOI: 10.1080/10485250701830113
Publication Frequency: 8 issues per year
Published in: journal Journal of Nonparametric Statistics, Volume 20, Issue 1 January 2008 , pages 19 - 37
Formats available: HTML (English) : PDF (English)
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Abstract

This study explores issues related to one-sample nonparametric tests for the median of a continuous distribution when the sample is collected via size-bias of a known order. A general principle on how to construct the reference distribution of a given test statistic is presented. Following this principle, we create new bias-corrected nonparametric testing procedures. Computationally intensive, exact P-values are available for a small sample. When the sample size is large, P-values can be easily estimated by the asymptotic approximation developed here. Power functions of these tests are investigated in both small- and large-sample cases and consistency is shown to hold under fairly general conditions. The tests' performances are then compared via asymptotic relative efficiency under four theoretical distributions.
Keywords: nonparametric test; permutation test; testing median; size-biased sample; weighted distribution; asymptotic relative efficiency
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