Date of Award

12-2017

Degree Name

Doctor of Philosophy

Department

Statistics

First Advisor

Dr. Joshua D. Naranjo

Second Advisor

Dr. Joseph McKean

Third Advisor

Dr. Georgiana Onicescu

Fourth Advisor

Dr. Karen Villarente Rosales

Keywords

Clinical Equivalence, shift model, shift-scale model, F-Test, Equivalence test, two one-sided tests

Abstract

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.

Access Setting

Dissertation-Open Access

Download

Share

COinS