统计与管理学院2017年学术报告第31期

【主  题】Efficient tests to demonstrate the similarity of dose response curves

【报告人】Frank Bretz, 博士

Novartis

【时  间】 2017年05月18日（星期四）16:00－17:00

【地  点】 上海财经大学统计与管理学院大楼1208室

【摘  要】This talk investigates the problem whether the difference between two parametric models describing the relation between a response variable and several covariates in two different groups is practically irrelevant, such that inference can be performed on the basis of the pooled sample. We develop a new statistical test to demonstrate equivalence of regression curves based on the asymptotic properties of a suitable metric measuring the distance between any two regression models. Using a non-standard bootstrap test, data has to be generated under the null hypothesis, which implicitly defines a manifold for the parameter vector. The results are illustrated by means of a simulation study and a data example.

【嘉宾简介】Frank Bretz joined Novartis in 2004, where he is currently Global Head of the Statistical Methodology and Consulting group. He has supported the methodological development in various areas of drug development, including dose-finding, multiple comparisons, and adaptive designs. Since 2011 he is an Adjunct Professor at the Shanghai University of Finance and Economics.

【邀请人】 尤进红