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Power comparison of non-parametric tests: Small-sample properties from Monte Carlo experiments

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  • Hisashi Tanizaki

Abstract

Non-parametric tests that deal with two samples include scores tests (such as the Wilcoxon rank sum test, normal scores test, logistic scores test, Cauchy scores test, etc.) and Fisher's randomization test. Because the non-parametric tests generally require a large amount of computational work, there are few studies on small-sample properties, although asymptotic properties with regard to various aspects were studied in the past. In this paper, the non-parametric tests are compared with the t -test through Monte Carlo experiments. Also, we consider testing structural changes as an application in economics.

Suggested Citation

  • Hisashi Tanizaki, 1997. "Power comparison of non-parametric tests: Small-sample properties from Monte Carlo experiments," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(5), pages 603-632.
    • Handle: RePEc:taf:japsta:v:24:y:1997:i:5:p:603-632
    DOI: 10.1080/02664769723576
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    Cited by:

    1. Nadine Chlass & Jens J. Krueger, 2007. "Small Sample Properties of the Wilcoxon Signed Rank Test with Discontinuous and Dependent Observations," Jena Economics Research Papers 2007-032, Friedrich-Schiller-University Jena.
    2. Citlali Calderon & Lorena Carrete & Jorge Vera-Martínez & María Esther Gloria-Quintero & María del Socorro Romero-Figueroa, 2021. "A Social Marketing Intervention to Improve Treatment Adherence in Patients with Type 1 Diabetes," IJERPH, MDPI, vol. 18(7), pages 1-14, March.
    3. Kateřina Macháčová & Hana Vaňková & Iva Holmerová & Inna Čábelková & Ladislav Volicer, 2018. "Ratings of activities of daily living in nursing home residents: comparison of self- and proxy ratings with actual performance and the impact of cognitive status," European Journal of Ageing, Springer, vol. 15(4), pages 349-358, December.
    4. Markus Neuh�user, 2015. "Combining the t test and Wilcoxon's rank-sum test," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(12), pages 2769-2775, December.
    5. Serguei Rouzinov & André Berchtold, 2022. "Regression-Based Approach to Test Missing Data Mechanisms," Data, MDPI, vol. 7(2), pages 1-28, January.
    6. Kai Wang & Manikandan Narayanan & Hua Zhong & Martin Tompa & Eric E Schadt & Jun Zhu, 2009. "Meta-analysis of Inter-species Liver Co-expression Networks Elucidates Traits Associated with Common Human Diseases," PLOS Computational Biology, Public Library of Science, vol. 5(12), pages 1-16, December.

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