Event Summary:
A one-day workshop organized by the Center for Interdisciplinary Research and
Consulting at the University of Maryland, Baltimore County (UMBC), and the
Center for Innovative Study Design (CISD) at Stanford University in the field of Clinical Trials and Regulatory Science.
Registration is now closed
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Organizing Committee:
Yi Huang (UMBC)
Nagaraj Neerchal (UMBC)
Bimal Sinha (UMBC)
Tze Lai (Stanford)
Phillip Lavori (Stanford)
Ying Lu (Stanford)
Jie Chen (Novartis)
Joseph Heyse (Merck)
For more information:
Please contact Dr. Yi Huang, Department of Mathematics and
Statistics, University of Maryland Baltimore County (UMBC),
1000 Hilltop Circle, Baltimore, MD 21250.
E-Mail: yihuang@umbc.edu.
For any Technical difficulties Please contact Zana Coulibaly at czana1@umbc.edu.
Participant Information
Yi Tsong from FDA.
Paper: Asymptotic tests of equivalence with variance-adjusted margins With normal endpoints
Equivalence assessment of difference of normal means with margin adjusted for variance of the reference product is often required in bioequivalence and biosimilar studies. The equivalence assessment is often carried out by comparing the confidence interval (CI) against the margins or by testing the two one-sided hypotheses (TOST). In the TOST, statisticians may derive the test statistic using unrestricted standard error or standard error restricted to null hypothesis. The regular CI approach is consistent with TOST with unrestricted standard error. In any of the setting, the standardized test statistic converges to standard normal distribution. However, the rate of convergence may be different. Furthermore, type I error rate control may also be different among the approaches for small unbalanced samples. In this presentation, I will be sharing the results of a 2015 FDA intern research project.