A nonparametric test for similarity of marginals—With applications to the assessment of population bioequivalence |
| |
Authors: | Gudrun Freitag Claudia Czado Axel Munk |
| |
Institution: | 1. Institut für Mathematische Stochastik, Georg-August Universität Göttingen, Maschmühlenweg 8-10, 37073 Göttingen, Germany;2. Technische Universität München, Zentrum Mathematik, Germany |
| |
Abstract: | In this paper we suggest a completely nonparametric test for the assessment of similar marginals of a multivariate distribution function. This test is based on the asymptotic normality of Mallows distance between marginals. It is also shown that the n out of n bootstrap is weakly consistent, thus providing a theoretical justification to the work in Czado, C. and Munk, A. 2001. Bootstrap methods for the nonparametric assessment of population bioequivalence and similarity of distributions. J. Statist. Comput. Simulation 68, 243–280]. The test is extended to cross-over trials and is applied to the problem of population bioequivalence, where two formulations of a drug are shown to be similar up to a tolerable limit. This approach was investigated in small samples using bootstrap techniques in Czado, C., Munk, A. 2001. Bootstrap methods for the nonparametric assessment of population bioequivalence and similarity of distributions. J. Statist. Comput. Simulation 68, 243–280], showing that the bias corrected and accelerated bootstrap yields a very accurate and powerful finite sample correction. A data example is discussed. |
| |
Keywords: | Bioequivalence Cross-over trials Hadamard derivative Limit law Multivariate empirical process Pre&ndash post comparison |
本文献已被 ScienceDirect 等数据库收录! |
|