Equivalence Tests: A Practical Primer for t-Tests, Correlations, and Meta-Analyses

Scientists should be able to provide support for the absence of a meaningful effect. Currently researchers often incorrectly conclude an effect is absent based a non-significant result. A widely recommended approach within a Frequentist framework is to test for equivalence. In equivalence tests, such as the Two One-Sided Tests (TOST) procedure discussed in this article, an upper and lower equivalence bound is specified based on the smallest effect size of interest. The TOST procedure can be used to statistically reject the presence of effects large enough to be considered worthwhile. This practical primer with accompanying spreadsheet and R package enables psychologists to easily perform equivalence tests (and power analyses) by setting equivalence bounds based on standardized effect sizes, and provides recommendations to pre-specify equivalence bounds. Extending your statistical toolkit with equivalence tests might very well be the easiest way for psychologists to improve their statistical and theoretical inferences.