Hybrid likelihood methods

混合似然法

• 批准号: 0505201
• 负责人: Ian McKeague
• 金额: --
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0505201&HistoricalAwards=false
• 关键词: Hybrid; likelihood; methods

ABSTRACTProp ID: DMS-0505201 PI: McKeague, Ian W.NSF Program: STATISTICS Institution: Columbia University Title: Hybrid likelihood methods Empirical likelihood is being extended in three directions: to allow for plug-in estimates of nuisance parameters in estimating equations, slower than root-n rates of convergence, and settingsin which there are a relatively large number of estimating equationscompared to the sample size. This work is motivated in partby the need to more effectively compare survival distributions in clinical trials and cohort studies.Methods of finding confidence intervals for split points, as represented by jumps in parametric regression models withinbroader semiparametric models, are also being investigated. This involves developing cube-root asymptotics for hybrid likelihood methods. A new confidence set is constructed by inverting ahybrid likelihood ratio statistic. This part of the project is motivated by an application to the development of a phosphorus threshold standard for the Everglades. Finally, hybrid likelihood techniques are being developed for use in HIV vaccine efficacy trials in which it is important to take into account dependence of the relative risk of infection on the divergence of infecting HIV viruses.Hybrid likelihood provides a unified way of looking at techniquesthat adapt a nonparametric likelihood based approach in some way, for example through the use of plug-in estimates for nuisance parameters, or by the use of a likelihood derived from a working (but not "true") model. The use of hybrid likelihood has become increasinglycommon in recent years and is attractive in many applied areas because it combines the power of likelihood based methods with a pragmatic sense of the need to find tractable and easily implementedsolutions to complex statistical problems. The investigator is extending the scope of hybrid likelihood methods in a variety of settings. Methodological work is conducted on three specific topics:empirical likelihood with applications in survival analysis,confidence intervals for split points with application to the estimation of pollution thresholds, and comparison of mark-specific relative risks with application to the detection ofviral divergence in HIV vaccine efficacy trials.

Prop ID：dms-0505201 PI：McKeague，Ian W.NSF程序：统计机构：哥伦比亚大学标题：混合似然方法经验似然法正朝着三个方向扩展：允许插入估计方程中滋扰参数的估计，收敛速度慢于根n，以及与样本大小相比存在相对较大数量的估计方程的环境。这项工作的部分动机是需要更有效地比较临床试验和队列研究中的生存分布。寻找分割点的可信区间的方法也在研究中，如参数回归模型在更广泛的半参数模型中的跳跃所代表的。这涉及到为混合似然方法开发立方根渐近性。通过对混合似然比统计量进行倒置，构造了一种新的置信度。该项目的这一部分的动机是应用于制定大沼泽地的磷阈值标准。最后，混合似然技术正被开发用于艾滋病毒疫苗效力试验，其中重要的是考虑感染的相对风险与感染艾滋病毒病毒的差异的相关性。混合似然技术提供了一种统一的方法来看待以某种方式适应基于非参数似然方法的技术，例如通过使用对滋扰参数的插件估计，或者通过使用从工作(但不是“真实的”)模型中获得的似然。近年来，混合似然方法的使用变得越来越普遍，并在许多应用领域引起了人们的兴趣，因为它结合了基于似然方法的强大功能和需要为复杂统计问题找到易于处理和实施的解决方案的实际意义。研究人员正在各种环境中扩展混合似然方法的范围。方法论工作围绕三个具体主题进行：经验似然性及其在生存分析中的应用、分离点的可信区间及其在污染阈值估计中的应用、以及标记特定的相对风险与在HIV疫苗有效性试验中应用于病毒分歧检测的比较。