Equivalence Testing

Definition: Equivalence tests statistically assess the null hypothesis that a given effect exceeds a minimum criterion to be considered meaningful. Thus, rejection of the null hypothesis provides evidence of a lack of (meaningful) effect. Based upon frequentist statistics, equivalence tests work by specifying equivalence bounds: a lower and upper value that reflect the smallest effect size of interest. Two one-sided t-tests are then conducted against each of these equivalence bounds to assess whether effects that are deemed meaningful can be rejected (see Schuirmann, 1972; Lakens et al., 2018; 2020).

Related terms: Equivalence bounds, Falsification, Frequentist analyses, Inference by confidence intervals, Null Hypothesis Significance Testing (NHST), Smallest effect size of interest (SESOI), TOST procedure., TOSTER

References: Lakens et al. (2018), Lakens et al. (2020), & Schuirmann (1987)

Drafted and Reviewed by: Charlotte R. Pennington, Bradley Baker, James E. Bartlett, Jamie P. Cockcroft, Tobias Wingen, Flávio Azevedo

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