Consistency of the Bootstrap Procedure in Individual Bioequivalence

Recently, new concepts have been proposed for assessing
bioequivalence of two drug formulations, namely the so-called
population and individual bioequivalence. Using moment-based and
probability-based measures for evaluating the proposed
bioequivalence concepts, criteria have been formulated to decide
whether two formulations should be regarded as bioequivalent or
not. This decision has of course to be based on an adequate
statistical method where the Food and Drug Administration (FDA)
guidance (1997) recommends the use of a bootstrap percentile
interval. In this paper, we discuss theoretical properties such as
consistency and accuracy of the recommended bootstrap intervals. We
focus our investigations on the concept of individual
bioequivalence and here especially on the scaled versions of the
moment-based as well as the probability-based measures as
recommended by the FDA. As estimates for the former, we consider
those obtained from an according analysis of variance and
restricted maximum likelihood estimators under mixed effect models,
where an unbiased estimator of the latter can be derived from the
corresponding relative frequencies.