IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v42y2015i12p2769-2775.html
   My bibliography  Save this article

Combining the t test and Wilcoxon's rank-sum test

Author

Listed:
  • Markus Neuh�user

Abstract

In the two-sample location-shift problem, Student's t test or Wilcoxon's rank-sum test are commonly applied. The latter test can be more powerful for non-normal data. Here, we propose to combine the two tests within a maximum test. We show that the constructed maximum test controls the type I error rate and has good power characteristics for a variety of distributions; its power is close to that of the more powerful of the two tests. Thus, irrespective of the distribution, the maximum test stabilizes the power. To carry out the maximum test is a more powerful strategy than selecting one of the single tests. The proposed test is applied to data of a clinical trial.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:japsta:v:42:y:2015:i:12:p:2769-2775
    DOI: 10.1080/02664763.2015.1070809
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2015.1070809
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2015.1070809?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. R. Clifford Blair & James J. Higgins, 1980. "A Comparison of the Power of Wilcoxon's Rank-Sum Statistic to that of Student'st Statistic Under Various Nonnormal Distributions," Journal of Educational and Behavioral Statistics, , vol. 5(4), pages 309-335, December.
    3. Erich Lehmann, 2009. "Parametric versus nonparametrics: two alternative methodologies," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(4), pages 397-405.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. 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.
    3. 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.
    4. David C Young & Tina Delaney & B Anthony Armson & Cora Fanning, 2020. "Oral misoprostol, low dose vaginal misoprostol, and vaginal dinoprostone for labor induction: Randomized controlled trial," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-17, January.
    5. 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.
    6. Serguei Rouzinov & André Berchtold, 2022. "Regression-Based Approach to Test Missing Data Mechanisms," Data, MDPI, vol. 7(2), pages 1-28, January.
    7. Amitava Mukherjee & Marco Marozzi, 2019. "A class of percentile modified Lepage-type tests," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(6), pages 657-689, August.
    8. repec:sip:wpaper:12-026 is not listed on IDEAS

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:japsta:v:42:y:2015:i:12:p:2769-2775. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.