Stratified two‐sample design: A review on nonparametric methods

In this article, a comparison between the most promising nonparametric tests in a two‐sample stratified design for practical uses is performed. We compared methods that exhibit good small‐sample properties in order to be used with the most common stratum sizes. From the literature we identified as p...

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Bibliographic Details
Published inApplied stochastic models in business and industry Vol. 36; no. 5; pp. 959 - 973
Main Authors Carrozzo, Eleonora, Arboretti, Rosa, Ceccato, Riccardo, Salmaso, Luigi
Format Journal Article
LanguageEnglish
Published Bognor Regis Wiley Subscription Services, Inc 01.09.2020
Subjects
industrial statistics
Nonparametric statistics
nonparametric stratified tests
Permutations
Rank tests
stratified analysis
Test procedures
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Summary:In this article, a comparison between the most promising nonparametric tests in a two‐sample stratified design for practical uses is performed. We compared methods that exhibit good small‐sample properties in order to be used with the most common stratum sizes. From the literature we identified as promising the following solutions: the aligned rank test, a small‐sample approximation for the ANOVA‐type statistic based on an unweighted average of all the distributions, and an asymptotic permutation distribution for the Wald‐type statistic. We also developed a permutation version of the aligned rank test and another permutation testing procedure based on the Mann‐Whitney statistic using the nonparametric combination procedure. All selected methods were compared by means of a simulation study. The results show that the aligned rank test and its permutation version perform better in most of the considered situations. Data from a genuine industrial problem were used for illustration purposes and to confirm the simulation results.
ISSN:1524-1904
1526-4025
DOI:10.1002/asmb.2557