Detection of outlying data in bioavailability/bioequivalence studies
JP Liu, CS Weng - Statistics in Medicine, 1991 - Wiley Online Library
JP Liu, CS Weng
Statistics in Medicine, 1991•Wiley Online LibraryThis paper considers the problem of detecting outlying data in bioavailability/bioequivalence
studies. We define outlying subjects as those whose responses in bioavailability to all
formulations differ from the rest of the subjects. We also define an outlying observation as
the response in bioavailability of a subject to a particular formulation which is grossly
different from the average bioavailability of that formulation calculated from all subjects. We
propose two test procedures. The first, based on two‐sample Hotelling T2, is to detect …
studies. We define outlying subjects as those whose responses in bioavailability to all
formulations differ from the rest of the subjects. We also define an outlying observation as
the response in bioavailability of a subject to a particular formulation which is grossly
different from the average bioavailability of that formulation calculated from all subjects. We
propose two test procedures. The first, based on two‐sample Hotelling T2, is to detect …
Abstract
This paper considers the problem of detecting outlying data in bioavailability/bioequivalence studies. We define outlying subjects as those whose responses in bioavailability to all formulations differ from the rest of the subjects. We also define an outlying observation as the response in bioavailability of a subject to a particular formulation which is grossly different from the average bioavailability of that formulation calculated from all subjects. We propose two test procedures. The first, based on two‐sample Hotelling T2, is to detect possible outlying subjects. The second, based on residuals from formulation means, is to identify possible outlying observations within subjects. Both procedures take into account the covariance structure of the responses to formulations, dependence of test statistics, and multiplicity of test procedures. We apply the Monte Carlo or bootstrap simulation to evaluate the sampling distributions of test statistics. An example from a 3‐way crossover bioequivalence study illustrates the two procedures.
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