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What to make of equivalence testing with a post-specified margin?

Harlan Campbell, Paul Gustafson

2021Meta-Psychology13 citationsDOIOpen Access PDF

Abstract

In order to determine whether or not an effect is absent based on a statistical test, the recommended frequentist tool is the equivalence test. Typically, it is expected that an appropriate equivalence margin has been specified before any data are observed. Unfortunately, this can be a difficult task. If the margin is too small, then the test's power will be substantially reduced. If the margin is too large, any claims of equivalence will be meaningless. Moreover, it remains unclear how defining the margin afterwards will bias one's results. In this short article, we consider a series of hypothetical scenarios in which the margin is defined post-hoc or is otherwise considered controversial. We also review a number of relevant, potentially problematic actual studies from the clinical trials research, with the aim of motivating a critical discussion as to what is acceptable and desirable in the reporting and interpretation of equivalence tests.

Topics & Concepts

Margin (machine learning)Equivalence (formal languages)Frequentist inferencePost hocStatistical hypothesis testingComputer scienceEconometricsMathematicsStatisticsMachine learningArtificial intelligenceBayesian probabilityMedicineBayesian inferenceDiscrete mathematicsDentistryStatistical Methods in Clinical TrialsMeta-analysis and systematic reviewsHealth Systems, Economic Evaluations, Quality of Life
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