  In medical device comparison studies, equivalency test is commonly used to
demonstrate two measurement methods agree up to a pre-specified performance
goal based on the paired repeated measures. Such equivalency test often
involves controlling the absolute differences that depend on both the mean and
variance parameters, and poses some challenges for statistical analysis. For
example, for the oximetry comparison study that motivates our research, FDA has
clear guidelines approving an investigational pulse oximeter in comparison to a
standard oximeter via testing the root mean squares (RMS), a composite measure
of both mean and variance parameters. For the hypothesis testing of this
composite measure, existing methods have been either exploratory or relying on
the large-sample normal approximation with conservative and unsatisfactory
performance. We develop a novel generalized pivotal test to rigorously and
accurately test the system equivalency based on RMS. The proposed method has
well-controlled type I error and favorable performance in our extensive
numerical studies. When analyzing data from an oximetry comparison study,
aiming to demonstrate performance equivalency between an FDA-cleared oximetry
system and an investigational system, our proposed method resulted in a highly
significant test result strongly supporting the system equivalency. We also
provide efficient R programs for the proposed method in a publicly available R
package. Considering that many practical equivalency studies of diagnostic
devices are of small to medium sizes, our proposed method and software timely
bridge an existing gap in the field.
