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

Oladugba Abimibola Victoria (), Obasi Ajali John and Asogwa Oluchukwu Chukwuemeka
Additional contact information
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 .

Statistics in Transition New Series, 2022, vol. 23, issue 4, 77-90

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.

Keywords: randomisation test; repeated measures design; sensitivity; robustness; Monte Carlo (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/stattrans-2022-0043 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:23:y:2022:i:4:p:77-90:n:3

DOI: 10.2478/stattrans-2022-0043

Access Statistics for this article

Statistics in Transition New Series is currently edited by Włodzimierz Okrasa

More articles in Statistics in Transition New Series from Statistics Poland
Bibliographic data for series maintained by Peter Golla ().