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A unified approach to permutation testing for equivalence

Author

Listed:
  • Rosa Arboretti

    (University of Padova)

  • Fortunato Pesarin

    (University of Padova)

  • Luigi Salmaso

    (University of Padova)

Abstract

The notion of testing for equivalence of two treatments is widely used in clinical trials, pharmaceutical experiments, bioequivalence and quality control. It is traditionally operated within the intersection–union principle (IU). According to this principle the null hypothesis is stated as the set of effects the differences $$\delta$$ δ of which lie outside a suitable equivalence interval and the alternative as the set of $$\delta$$ δ that lie inside it. In the literature related solutions are essentially based on likelihood techniques, which in turn are rather difficult to deal with. A recently published paper goes beyond most of likelihood limitations by using the IU approach within the permutation theory. One more paper, based on Roy’s union–intersection principle (UI) within the permutation theory, goes beyond some limitations of traditional two-sided tests. Such UI approach, effectively a mirror image of IU, assumes a null hypothesis where $$\delta$$ δ lies inside the equivalence interval and an alternative where it lies outside. Since testing for equivalence can rationally be analyzed by both principles but, as the two differ in terms of the mirror-like roles assigned to the hypotheses under study, they are not strictly comparable. The present paper’s main goal is to look into these problems and provide a sort of comparative analysis of both by highlighting the related requirements, properties, limitations, difficulties, and pitfalls so as to get practitioners properly acquainted with their correct use in practical contexts.

Suggested Citation

  • Rosa Arboretti & Fortunato Pesarin & Luigi Salmaso, 2021. "A unified approach to permutation testing for equivalence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 1033-1052, September.
    • Handle: RePEc:spr:stmapp:v:30:y:2021:i:3:d:10.1007_s10260-020-00548-0
    DOI: 10.1007/s10260-020-00548-0
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    References listed on IDEAS

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    1. Arnold Janssen & Stefan Wellek, 2010. "Exact linear rank tests for two‐sample equivalence problems with continuous data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(4), pages 482-504, November.
    2. Sen, Pranab K. & Tsai, Ming-Tien, 1999. "Two-Stage Likelihood Ratio and Union-Intersection Tests for One-Sided Alternatives Multivariate Mean with Nuisance Dispersion Matrix," Journal of Multivariate Analysis, Elsevier, vol. 68(2), pages 264-282, February.
    3. Fortunato Pesarin, 2015. "Some Elementary Theory of Permutation Tests," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(22), pages 4880-4892, November.
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    Cited by:

    1. Mirosław Krzyśko & Łukasz Smaga, 2024. "Application of distance standard deviation in functional data analysis," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 18(2), pages 431-454, June.

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