Symposium on Case Studies in Bayesian Statistics; September 26-27, 1997; Pittsburgh, PA

贝叶斯统计学案例研究专题讨论会罗伯特·E·卡斯·卡内基梅隆大学将于1997年9月26日星期五和9月27日星期六在宾夕法尼亚州匹兹堡的卡内基-梅隆大学举行题为“贝叶斯统计学案例研究4”的专题讨论会。研讨会将包括四个关于贝叶斯方法在一系列医疗和工业应用中的应用的扩展演讲。更具体地说，所选演讲的主题包括：乳腺癌风险建模、药物开发中的药代动力学建模、客户价值分析问题，以及功能磁共振成像的统计方面。在这些应用中，统计学家是研究小组不可或缺的成员。还将举行投稿海报会议。专题讨论会的目标是：(1)确定并集中注意妨碍应用贝叶斯方法的具体实施和理论问题，并确定候选解决办法；(2)提供一个论坛，在具体研究项目的背景下探讨统计理论与实践之间的相互作用；(3)提供一个小型会议氛围，使初级研究人员和研究生能够与有经验的研究人员一起探索实质性的贝叶斯应用；以及(4)编写一册文件齐全的案例研究和数据集，供应用统计和其他量化领域的研究人员、从业人员、教育工作者和学生使用。随着越来越多的背景信息可供科学家进行调查，在设计研究和分析数据时有效利用先前的知识是很重要的。贝叶斯统计方法就是为此量身定做的。贝叶斯统计理论和计算最近取得了许多进展，但科学会议很少花大量时间讨论应用。这次研讨会的目的是将注意力集中在贝叶斯统计的应用上。其目的是阐明理论和实践之间的相互作用，从而确定成功的方法，并为未来的研究指明重要方向。

Symposium on Case Studies in Bayesian Statistics Robert E. Kass Carnegie Mellon University A symposium entitled ``Case Studies in Bayesian Statistics 4'' will be held at Carnegie-Mellon University in Pittsburgh, Pennsylvania, on Friday September 26 and Saturday September 27, 1997. The symposium will include four extended presentations of applications of Bayesian methods to a range of medical and industrial applications. More specifically, topics of the selected presentations inalude: modeling for risk of breast cancer, pharmacokinetic modeling in drug development, problems of customer value analysis, and statistical aspects of functional MRI. In these applications the statistician was an integral member of the research team. A contributed poster session will also be held. The objectives of the symposium are to: (i) identify and focus attention on specific implementation and theoretical problems that hinder applications of Bayesian methods, and to identify candidate solutions; (ii) provide a forum in which the interplay between statistical theory and practice will be explored in the context of concrete research projects; (iii) provide a small-meeting atmosphere within which junior investigators and graduate students can explore substantial Bayesian applications with experienced researchers; and (iv) produce a volume containing well-documented case studies and data sets suitable for use by researchers, practitioners, educators and students of applied statistics and other quantitative fields. As increasingly much background information becomes available to scientists undertaking an investigation, it is important to utilize previous knowledge effectively in designing studies and analyzing data. Bayesian statistical methods are tailored to this purpose. There have been many recent advances in Bayesian statistical theory and computation, b ut scientific meetings rarely spend substantial time discussing applications. The purpose of this symposium is to concentrate attention solely on applications of Bayesian statistics. The goal is to elucidate the interplay between theory and practice and thereby identify successful methods and indicate important directions for future research.