Sample size analysis for two-sample linear rank tests

Klein I, Doll M (2022)

Publication Language: English

Publication Type: Journal article

Publication year: 2022

Journal

Communications in Statistics-Theory and Methods Taylor & Francis: STM, Behavioural Science and Public Health Titles / Taylor & Francis

URI: https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2068029

DOI: 10.1080/03610926.2022.2068029

Open Access Link: https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2068029

Abstract

Sample size analysis is a key part of the planning phase of any research. So far, however, hardly any literature focuses on sample size analysis methods for two-sample linear rank tests, although these methods have optimal properties for different distributions. This article provides a new sample size analysis method for linear rank tests for location shift alternatives based on score-generating functions. Results show a slightly anti-conservative behavior, no severe risk of an occurring circular argument at small to moderate variances of the population’s distribution, and good performance compared to alternate sample size analysis methods for the most well-known linear rank test, the Wilcoxon-Mann-Whitney test.

Authors with CRIS profile

Ingo Klein Fachbereich Wirtschaftswissenschaften Monika Lieb Lehrstuhl für Statistik und Ökonometrie

How to cite

APA:

Klein, I., & Doll, M. (2022). Sample size analysis for two-sample linear rank tests. Communications in Statistics-Theory and Methods. https://dx.doi.org/10.1080/03610926.2022.2068029

MLA:

Klein, Ingo, and Monika Doll. "Sample size analysis for two-sample linear rank tests." Communications in Statistics-Theory and Methods (2022).

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