Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Yujing Jiang, Mei-Ling Ting Lee, Xin He, Bernard Rosner, Jun Yan
Title: Wilcoxon Rank-Based Tests for Clustered Data with R Package clusrank
Abstract: Wilcoxon rank-based tests are distribution-free alternatives to the popular two-sample and paired t tests. For independent data, they are available in several R packages such as stats and coin. For clustered data, in spite of the recent methodological developments, there did not exist an R package that makes them available at one place. We present a package clusrank where the latest developments are implemented and wrapped under a unified user-friendly interface. With different methods dispatched based on the inputs, this package offers great flexibility in rank-based tests for various clustered data. Exact tests based on permutations are also provided for some methods. Details of the major schools of different methods are briefly reviewed. Usages of the package clusrank are illustrated with simulated data as well as a real dataset from an ophthalmological study. The package also enables convenient comparison between selected methods under settings that have not been studied before and the results are discussed.

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Paper: Wilcoxon Rank-Based Tests for Clustered Data with R Package clusrank     Download PDF (Downloads: 510)
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clusrank_1.0-0.tar.gz: R source package Download (Downloads: 35; 37KB)
v96i06.R: R replication code Download (Downloads: 30; 6KB)
v96i06-simulation.R: R simulation code Download (Downloads: 30; 51KB)

DOI: 10.18637/jss.v096.i06

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.