IDEAS home Printed from https://ideas.repec.org/a/vrs/stintr/v23y2022i4p77-90n3.html
   My bibliography  Save this article

Robustness of randomisation tests as alternative analysis methods for repeated measures design

Author

Listed:
  • Oladugba Abimibola Victoria

    (Department of Statistics, University of Nigeria, Nsukka, Nigeria .)

  • Obasi Ajali John

    (Department of Statistics, University of Nigeria, Nigeria .)

  • Asogwa Oluchukwu Chukwuemeka

    (Department of Mathematics/Computer Science/Statistics and Informatics, Alex Ekwueme Federal University Ndufu Alike Ikwo, Nigeria .)

Abstract

Randomisation tests (R-tests) are regularly proposed as an alternative method of hypothesis testing when assumptions of classical statistical methods are violated in data analysis. In this paper, the robustness in terms of the type-I-error and the power of the R-test were evaluated and compared with that of the F-test in the analysis of a single factor repeated measures design. The study took into account normal and non-normal data (skewed: exponential, lognormal, Chi-squared, and Weibull distributions), the presence and lack of outliers, and a situation in which the sphericity assumption was met or not under varied sample sizes and number of treatments. The Monte Carlo approach was used in the simulation study. The results showed that when the data were normal, the R-test was approximately as sensitive and robust as the F-test, while being more sensitive than the F-test when data had skewed distributions. The R-test was more sensitive and robust than the F-test in the presence of an outlier. When the sphericity assumption was met, both the R-test and the F-test were approximately equally sensitive, whereas the R-test was more sensitive and robust than the F-test when the sphericity assumption was not met.

Suggested Citation

  • Oladugba Abimibola Victoria & Obasi Ajali John & Asogwa Oluchukwu Chukwuemeka, 2022. "Robustness of randomisation tests as alternative analysis methods for repeated measures design," Statistics in Transition New Series, Polish Statistical Association, vol. 23(4), pages 77-90, December.
    • Handle: RePEc:vrs:stintr:v:23:y:2022:i:4:p:77-90:n:3
    DOI: 10.2478/stattrans-2022-0043
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/stattrans-2022-0043
    Download Restriction: no
    File URL: https://libkey.io/10.2478/stattrans-2022-0043?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
    ---><---

    References listed on IDEAS

    as
    1. Kenneth J Berry & Janis E Johnston & Paul W Mielke Jr & Howard W Mielke & Lindsay A Johnston, 2018. "Permutation Statistical Methods: Calculation Efficiencies," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 4(3), pages 63-77, January.
    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.

      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:vrs:stintr:v:23:y:2022:i:4:p:77-90:n:3. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

      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.