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Confidence intervals for ratios of AUCs in the case of serial sampling: a comparison of seven methods
Author(s) -
Jaki Thomas,
Wolfsegger Martin J.,
Ploner Meinhard
Publication year - 2008
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.321
Subject(s) - statistics , confidence interval , bioequivalence , sample size determination , sampling (signal processing) , type i and type ii errors , inference , statistical inference , nominal level , sampling design , mathematics , stage (stratigraphy) , coverage probability , computer science , medicine , pharmacokinetics , artificial intelligence , population , paleontology , environmental health , filter (signal processing) , computer vision , biology
Pharmacokinetic studies are commonly performed using the two‐stage approach. The first stage involves estimation of pharmacokinetic parameters such as the area under the concentration versus time curve (AUC) for each analysis subject separately, and the second stage uses the individual parameter estimates for statistical inference. This two‐stage approach is not applicable in sparse sampling situations where only one sample is available per analysis subject similar to that in non‐clinical in vivo studies. In a serial sampling design, only one sample is taken from each analysis subject. A simulation study was carried out to assess coverage, power and type I error of seven methods to construct two‐sided 90% confidence intervals for ratios of two AUCs assessed in a serial sampling design, which can be used to assess bioequivalence in this parameter. Copyright © 2008 John Wiley & Sons, Ltd.