Statistical Power for Equivalence Tests in Randomized Controlled Trials

There are instances where equivalences rather than differences are of interest. For instance, researchers may be interested in testing whether two versions of interventions are equivalent or whether an alternative but more cost-efficient program can provide similar outcomes (Lakens et al., 2018; Schuirmann, 1987). The literature on design and analytical strategies for equivalence testing has been limited (e.g., the prevalent equivalence test method does not include covariate adjustments, and the literature has not offered the correct statistical power formula). The purpose of this study is to advance the study and analysis for equivalence tests. First, this study extends the prevalent equivalence test method to designs with covariate adjustments to improve statistical power. Second, this study develops/validates the closed-form statistical power formula for equivalence tests and presents an optimal design framework for efficient sampling. Third, the methods have been implemented in the R package XXX to improve accessibility.