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Document type:
Zeitschriftenaufsatz 
Author(s):
Freitag, G., Czado, C., Munk, A. 
Title:
A nonparametric test for similarity of marginals - with applications to the assessment of population bioequivalence 
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 & Munk [12]. 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 [12], 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-post comparison 
Journal title:
Journal of Statistical Planning and Inference 
Year:
2007 
Journal volume:
137 
Journal issue:
Pages contribution:
697-711 
Reviewed:
ja 
Language:
en 
Status:
Verlagsversion / published 
Semester:
SS 08 
Format:
Text