ADAPTATION OF NEW STATISTICAL IDEAS FOR MEDICINE

描述：(改编自申请者的摘要)过去30年 几年来是方法论高度发展的时期 统计，具有比例似然、稳健等思想 估计、刀切/自举方法、经验贝叶斯技术、 纵向估计，EM算法变得重要。《长河》 本申请期限的目的是缩短转账时间 在有希望的理论/方法创新和他们的 生物统计学应用。这通常意味着链接新方法 建立了统计理论，并澄清了他们的数据- 分析优势。申请者的研究是从两个方面进行的 斯坦福大学统计系和医学院。四个领域 在这里建议作为即将进行的研究的焦点：使用 临床试验分析中的依从性数据；自举 方法特别是应用于偏差校正、荟萃分析、 预测和置信度椭球的构造；蒙特卡罗 用于事故类型分析的马尔可夫链估计量 由遗传标记数据产生的表格；以及实用公式 基于霍特林几何的同时假设检验 争论。其中一些工作将在合作中进行 随着生物医学研究人员致力于关节炎，艾滋病， 心血管疾病、遗传学研究和其他疾病 合规性测量特别有用。

DESCRIPTION: (Adapted from the applicant's abstract) The past thirty years have been a period of intense methodological development in statistics, with ideas such as proportional likelihood, robust estimation, jackknife/bootstrap methods, empirical Bayes techniques, longitudinal estimation, and EM algorithm becoming important. The long term purpose of this application is to shorten the transfer time between promising theoretical/methodological innovations and their biostatistical applications. This usually means linking the new methods to established statistical theory, and making clear their data- analytic advantages. the applicants' research is pursued from both the Stanford statistics department and medical school. Four areas are proposed here as focal points for forthcoming research: the use of complicance data in the analysis of clinical trials; bootstrap methods particularly as applied to bias-correction, metaanalysis, prediction, and the construction of confidence ellipsoids; Monte Carlo Markov chain estimators for the analysis of the type of contingency tables arising form genetic marker data; and practical formulas for simultaneous hypothesis testing, based on Hotelling's geometric arguments. Some of this work will be carried out in collaboration with biomedical researchers working on arthritis, AIDS, cardiovascular disease, genetics research, and other diseases in which compliance measurements are particularly useful.