Equivalence testing: A brief review

Sara King/ April 21, 2010/ Peer-reviewed Paper/ 0 comments

Equivalence testing has applications that include ingredient substitution and product matching. Statistical methods for determining equivalency were the subject of some interest in this journal prior to the Sensometrics 2008 conference (Bi, 2005; Meyners, 2007; Bi, 2007; Ennis, 2008a; Bi, 2008; Meyners, 2008; Ennis 2008b). A mini-symposium on equivalency at Sensometrics 2008 provided an opportunity for collegial discussion. Dr. D. M. Ennis presented methods for testing equivalency for binary data, normally distributed data with known variance, and normally distributed data with unknown variance. These tests are well described in recent publications (Ennis & Ennis, 2009a; 2009b). The two one-sided tests (TOST) procedure (Westlake, 1981; Schuirmann, 1987) is commonly used when testing equivalency. The TOST procedure is often used with tests that make parametric assumptions, but can be used with tests that do not make such assumptions (Zhou & Yuan, 2004). Ennis presented the adjusted noncentral chi-square (ANC) test as an alternative procedure to the TOST for normally distributed data with unknown variance. Drs. P. B. Brockhoff and M. Meyners accepted invitations to provide critical feedback on Ennis’s presentation. This review attempts to capture some of the key points.

Castura, J. C.  (2010). Equivalence testing: A brief review. Food Quality and Preference, 21, 257-258. https://doi.org/10.1016/j.foodqual.2009.12.002

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