Skip Navigation

Biometrika 2000 87(3):573-585; doi:10.1093/biomet/87.3.573
© 2000 by Biometrika Trust
This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Shao, J
Right arrow Articles by Pigeot, I
Right arrow Search for Related Content
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Consistency of the bootstrap procedure in individual bioequivalence

J ShaoZ, J KüblerZZ and I PigeotY

Z Department of Statistics, University of Wisconsin, 1210 West Dayton Street, Madison, Wisconsin 53706, USA E-mail: shao@stat.wisc.edu ZZ Bayer AG, PH-PD M CDPI/PE, D-42096 Wuppertal, Germany E-mail: juergen.kuebler.jk@bayer-ag.de Y Institute of Statistics, University of Munich, Ludwigstrasse 33, D-80539 Munich, Germany E-mail: pigeot@stat.uni-muenchen.de

Recently, the concepts of population and individual bioequivalence have been proposed for assessing the bioequivalence of two drug formulations. Moment-based and probability-based measures of bioequivalence have led to criteria for deciding whether two formulations should be regarded as bioequivalent or not. The US Food and Drug Administration (1997) guidance recommended the use of bootstrap percentile intervals for this purpose. In this paper, we discuss theoretical properties such as consistency and accuracy of the recommended bootstrap intervals. We concentrate on individual bioequivalence and especially on the scaled versions of the moment-based as well as the probability-based measures as recommended by the US Food and Drug Administration. As estimates for the former, we consider those obtained from an appropriate analysis of variance and restricted maximum likelihood estimators under mixed effect models, whereas an unbiased estimator of the latter can be derived from corresponding relative frequencies.

Key Words: bioequivalence; bootstrap percentile; consistency


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.