统计与管理学院2015年学术报告第3期
【主 题】Model-based dose finding under model uncertainty using general parametric models
【报告人】 Bretz Frank 博士
Novartis
【时 间】 2015年1月8日（星期四）10:00－11:00
【地 点】 上海财经大学统计与管理学院大楼1208室
【语 言】 英文
【摘 要】The statistical methodology for the design and analysis of clinical Phase II dose response studies, with related software implementation, is well developed for the case of a normally distributed, homoscedastic response considered for a single time point in parallel group study designs. In practice, however, binary, count, or time-to-event endpoints are encountered, typically measured repeatedly over time and sometimes in more complex settings like crossover study designs. In this presentation we develop an overarching methodology to perform efficient multiple comparisons and modeling for dose finding, under uncertainty about the dose-response shape, using general parametric models. The framework described here is quite broad and can be utilized in situations involving generalized non-linear models, linear and non-linear mixed effects models, Cox proportional hazards models, etc. Several examples illustrate the breadth of applicability of the results. For the analyses we developed the R add-on package DoseFinding, which provides a convenient interface to the general approach adopted here.
Reference:
Pinheiro, Bornkamp, Glimm, Bretz (2014) Model-based dose finding under model uncertainty using general parametric models. Statistics in Medicine 33(10): 1646?661
【邀请人】 尤进红
