SEMIPARAMETRIC REGRESSION TECHNIQUES FOR THE ANALYSIS OF BIOMEDICAL DATA

用于生物医学数据分析的半参数回归技术

• 批准号: 5211517
• 负责人: Joan G. Staniswalis
• 金额: --
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/5211517
• 关键词: computer simulation; human data; mathematical model; method development; statistics /biometry

The overall thrust of the research objectives is to make progress towards providing, for a wide variety of applications and experimental designs, a semi-parametric alternative to the popular parametric regression methods used in the analysis of data. Methodology is proposed for discrete and continuous data as well as for independent and correlated responses. The objectives are to study; i) nonparametric estimation of a regression function when the explanatory variable is discrete, ii) estimation of the dose effect given observations over time in a dose-response experiment, and nonparametric detection of interactions between dose and time, iii) estimation in conditionally specified distributions. Decisions and recommendations based on data analysis using the wrong parametric model are not reliable. Therein lies the need for the development of methodology for fitting semiparametric models to data. The basic research efforts outlined in this proposal include: I) theoretical work, ii) computer simulations to validate the procedures, and iii) application of the semiparametric methods to biomedical data obtained from researchers at Virginia Commonwealth University - Medical College of Virginia, The University of Texas M.D. Anderson Cancer Center, and The Eye Institute of the University of Wisconsin, Madison. This project also includes an undergraduate student mentorship and community outreach component. Undergraduate students in the Department of Mathematical Sciences will assist with the research projects and with mathematics outreach activities designed for the El Paso area Middle School students.

研究目标的总体目的是取得进步 为多种应用和实验设计提供 流行参数回归方法的半参数替代品 用于数据分析。 提出了用于离散和 连续数据以及独立和相关的响应。 这 目标是研究； i）回归的非参数估计 当解释变量离散时，功能，ii）估计 在剂量反应实验中随时间观察的剂量作用，并且 剂量与时间之间相互作用的非参数检测，iii） 估计有条件指定的分布。 基于数据分析的决策和建议使用错误 参数模型不是可靠的。 在其中需要 开发将半参数模型拟合到数据的方法。 这 本提案中概述的基础研究工作包括：i）理论 工作，ii）验证程序的计算机模拟，iii） 将半参数方法应用于从生物医学数据中获得的 弗吉尼亚联邦大学的研究人员 - 医学院 弗吉尼亚州，德克萨斯大学医学博士安德森癌症中心和眼睛 威斯康星大学麦迪逊大学。 这个项目也是如此 包括学生的指导和社区宣传 成分。 数学系的本科生 科学将协助研究项目和数学 为El Paso地区中学生设计的外展活动。