Modern Empirical Likelihood Methods in Biomedicine and Health

生物医学和健康中的现代经验似然法

• 批准号: 9014593
• 负责人: Albert Vexler
• 金额: $ 5万
• 依托单位: STATE UNIVERSITY OF NEW YORK AT BUFFALO
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9014593
• 关键词: Address; Adopted; Applications Grants; Area; Attention deficit hyperactivity disorder; Biometry; Biostatistical Methods; Books; Characteristics; Child; Clinical; Code; Computer software; Data; Data Analyses; Enzyme-Linked Immunosorbent Assay; Epidemiologic Studies; Epidemiology; Funding; Grant; Guidelines; Health; Instruction; Journals; Learning; Life; Literature; Malaria; Manuals; Manuscripts; Medical; Medicine; Methodology; Methods; Monte Carlo Method; Pneumonia; Positioning Attribute; Preparation; Procedures; Publications; Publishing; Reader; Research; Research Personnel; Risk; Scheme; Science; Scientist; Statistical Methods; Techniques; Testing; Time; Western Blotting; Writing; base; comparative; density; improved; innovation; interest; novel; novel strategies; research study; severe mood dysregulation; software development; statistics; tool

 DESCRIPTION (provided by applicant): Our proposal focuses on the preparation and writing of a book that will reflect a growing need for rigorous systematic presentations of classical and novel empirical likelihood (EL) approaches and their applications in Biomedicine and Health. With many examples, and data from biomedical studies, this book will explain newly advanced EL techniques applied to problems encountered in medical and epidemiological studies. A review of the modern scientific literature reveals the EL methodology is one of key components of highly efficient and robust non- and semi-parametric statistical tools in medical and epidemiological studies. The proposed book will cover basic/traditional EL techniques as well as novel approaches to performing non- and semi-parametric inferences that have been published in the literature, but have not published in a book format. The proposed book will also present efficient methods for constructing powerful distribution-free procedures to test composite hypotheses based on data that can be subject to different problems related to, e.g., missing values and limit of detections. The book will provide relevant software code for solving real data problems. The book material will be attractive and easily understandable to scientists who are new to the research area, including those who may not have a strong statistical background, and will also help attract statisticians interested in learning more about advanced topics. This book will also be aimed at biostatisticians who want to form a clear picture of various modern EL methods to extend and improve them. Drs. Vexler and Yu, PIs of this grant proposal, have been contacted by a well-known publisher that proved a great interest of receiving a book proposal related to the EL methods in Biomedicine and Health. The publisher pointed out that several independent experts in statistics, epidemiology and medicine indicated that the PIs have significantly contributed to the applied and theoretical EL methodology and the PIs are well positioned to write a book that will have an important place on the book lists of researchers in biomedical science. The authors of the proposed book apply for the grant to obtain an opportunity to write the book that requires time to be covered by the grant support. We shall collect, analyze and interpret relevant information published over the past 15 years in scientific journals, including the proposed book's authors' publications in Biometrics, Statistics in Medicine, Annals of Applied Statistics etc. Per each proposed method in the book, we will consider a large number of actual examples from medical and epidemiological studies to help the reader quickly learn novel empirical likelihood methods and apply them to real-life problems. We will aim to evaluate each described method in the contexts of theoretical and practical advantages and limitations. If fully successful, we believe that the proposed book has a great potential to be adopted as a primary manual regarding powerful statistical tools that change the practice of study planning for various clinical areas.

 描述（由申请人提供）：我们的建议侧重于准备和撰写一本书，这本书将反映对经典和新颖的经验似然（EL）方法及其在生物医学和健康中的应用的严格系统介绍的日益增长的需求。有许多例子，从生物医学研究的数据，这本书将解释新的先进EL技术应用于医学和流行病学研究中遇到的问题。 现代科学文献的回顾表明，EL方法是医学和流行病学研究中高效和强大的非和半参数统计工具的关键组成部分之一。拟议的书将涵盖基本/传统EL技术，以及新的方法来执行非和半参数推理，已在文献中发表，但没有出版的书的格式。这本书还将提出有效的方法，用于构建强大的无分布程序，以测试基于数据的复合假设，这些数据可能会遇到与以下方面有关的不同问题，例如，缺失值和检测限。本书将提供解决真实的数据问题的相关软件代码。这本书的材料将是有吸引力的，容易理解的科学家谁是新的研究领域，包括那些谁可能没有很强的统计背景，也将有助于吸引统计学家有兴趣了解更多关于先进的主题。这本书也将针对生物统计学家谁想要形成各种现代EL方法的清晰画面，以扩展和改进它们。 Drs. Vexler和Yu是这项资助提案的PI，一家知名出版商已经联系了他们，该出版商对收到一本与生物医学和健康中的EL方法相关的书籍提案非常感兴趣。出版商指出，几位统计学、流行病学和医学方面的独立专家表示，PI对应用和理论EL方法学做出了重大贡献，PI有能力撰写一本书，在生物医学科学研究人员的书单上占有重要地位。 建议的书的作者申请补助金，以获得一个机会来写这本书，需要时间来支付补助金的支持。我们将收集，分析和解释过去15年在科学期刊上发表的相关信息，包括建议书作者在生物统计学，医学统计学，应用统计学年鉴等方面的出版物。我们将考虑大量来自医学和流行病学研究的实际例子，以帮助读者快速学习新颖的经验似然方法并应用于解决现实生活中的问题我们将在理论和实践的优势和局限性的背景下评估每种描述的方法。如果完全成功，我们相信这本书有很大的潜力被采纳为一个主要的手册，关于强大的统计工具，改变实践的研究规划的各种临床领域。