Date of Award
Doctor of Philosophy
Dr. Joshua Naranjo
Dr. Joseph McKean
Dr. Georgiana Onicescu
Dr. Karen Villarente Rosales
Clinical Equivalence, shift model, shift-scale model, F-Test, Equivalence test, two one-sided tests
This study proposes a test for statistical equivalence of two measurements. Typically, a new measurement process Υ is compared to an existing or standard measurement process Χ. We are assuming that Χ and Υ are measurements on the same scale. The paired t-test may be used to check for significant difference between (Χ, Υ) pairs. However, the paired t-test is intended to detect shift-type relationships of the form Υ=Χ+δ1 and may have low power for scale-type relations of the form Υ=γΧ.
We propose a test that has reasonable power to detect either shift or scale-type relationships. Secondly, we propose a bioequivalence testing approach to swap the hypotheses so that statistical equivalence of the two measurements is the alternative hypothesis and bears the burden of proof. Rather than being the default conclusion in the absence of sufficient evidence, we conclude “clinical equivalence” only if there is evidence to support the claim that the magnitude of disagreement between the two measurements lies within specified limits.
Wanitjirattikal, Puntipa, "Statistical and Clinical Equivalence of Measurements" (2017). Dissertations. 3177.