TOPICS IN SEMIPARAMETRIC ANALYSIS OF SURVIVAL DATA

生存数据半参数分析主题

• 批准号: 2896544
• 负责人: GANG LI
• 金额: $ 9.85万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-08-01 至 2003-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2896544
• 关键词: data collection methodology /evaluation; human data; mathematical model; neoplasm /cancer epidemiology; statistics /biometry

DESCRIPTION (Adapted from Applicant's abstract): The objective of this research is to develop and apply new estimation, testing and regression procedures for analyzing left-truncated and right-censored survival data in the context of two medical studies, with the following aims: to develop more efficient and more flexible biostatistical methods that will be generally useful in research on cancer as well as in other research areas: and to apply the developed methods towards analysis of effects of bone marrow transplants (BMTAX) and comparison of BMT with traditional chemotherapy as a postremission treatment in patients with leukemia, and towards a study of efficacy of polyvalent melanoma cell vaccine in post- operative melanoma patients. The proposed research will be divided into three projects according to the following topics for analysis of left- truncated and right-censored data: 1) semiparametric estimation of survival probabilities: 2) nonparametric and semiparametric two-sample tests; and 3) semiparametric and nonparametric additive risk transformation models for survival regression. Semiparametric maximum likelihood estimation will be studied in project 1 and the developed estimate is expected to be more efficient that the traditional product limit estimate. In project 2, a quantily comparison function based on the percentile-percentile plot will be used to derive nonparametric and semiparametric two-sample tests which are expected to be more powerful than logrank type tests under crossing hazards alternatives. Additive risk transformation models will be introduced and studied in project 3, which will provide useful alternatives to the Cox proportional hazards mode when the proportional hazards assumption does not hold.

描述（改编自申请人的摘要）：此目的 研究是开发和应用新的估计，测试和回归 分析左截断和右审查生存数据的程序 在两项医学研究的背景下，以下目的： 开发更有效，更灵活的生物统计学方法 通常在癌症研究以及其他研究中有用 领域：并将开发的方法应用于分析的影响 骨髓移植（BMTAX）和BMT与传统的比较 化学疗法作为白血病患者的后放应治疗， 迈向多价黑色素瘤细胞疫苗在后期的疗效 手术黑色素瘤患者。 拟议的研究将分为 根据以下主题进行三个项目，用于分析左 截短和右审查的数据：1）半参数估计 生存概率：2）非参数和半参数两样本 测试； 3）半参数和非参数添加剂风险 生存回归的转化模型。 半参数最大 可能性估计将在项目1和开发的 估计预计将比传统产品更有效 限制估计。 在项目2中，基于数量的比较函数 百分位数的图将用于得出非参数和 半参数两样本测试，预计会更强大 在交叉危害替代方案下进行的logrank类型测试。 添加剂 风险转化模型将在项目3中引入和研究 这将为考克斯比例危害提供有用的替代方案 当比例危害假设不存在时。