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), TOSTER, TOST procedure.
References:
- Lakens, D., Scheel, A. M., & Isager, P. M. (2018). Equivalence testing for psychological research: A tutorial. Advances in Methods and Practices in Psychological Science, 1(2), 259–269. https://doi.org/10.1177/2515245918770963
- Lakens, D., McLatchie, N., Isager, P. M., Scheel, A. M., & Dienes, Z. (2020). Improving inferences about null effects with Bayes factors and equivalence tests. The Journals of Gerontology: Series B, 75(1), 45–57. https://doi.org/10.1093/geronb/gby065
- Schuirmann, D. J. (1987). A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability. Journal of Pharmacokinetics and Biopharmaceutics, 15, 657–680. https://doi.org/10.1007/BF01068419
Originally drafted by: Charlotte R. Pennington
Reviewed by: Bradley Baker, James E. Bartlett, Jamie P. Cockcroft, Tobias Wingen, Flávio Azevedo