TOPICS IN SEMIPARAMETRIC ANALYSIS OF SURVIVAL DATA

生存数据半参数分析主题

• 批准号: 6376805
• 负责人: GANG LI
• 金额: $ 10.99万
• 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/6376805
• 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 分析左截断和右删失生存数据的程序 在两项医学研究的背景下，目标如下： 开发更高效、更灵活的生物统计方法 通常可用于癌症研究以及其他研究 领域：并应用已开发的方法来分析 骨髓移植 (BMTAX) 以及 BMT 与传统的比较 化疗作为白血病患者的缓解后治疗，以及 研究多价黑色素瘤细胞疫苗在术后的功效 手术黑色素瘤患者。 拟议的研究将分为 三个项目根据以下主题进行分析左- 截断和右删失数据：1）半参数估计 生存概率：2）非参数和半参数双样本 测试； 3) 半参数和非参数加性风险 生存回归的转换模型。 半参数最大值 项目1将研究似然估计并开发出 预计比传统产品效率更高 极限估计。 项目2中，基于 百分位数-百分位数图将用于导出非参数和 预计更强大的半参数双样本检验 比交叉危险替代方案下的对数秩类型测试。 添加剂 项目3将引入和研究风险转换模型， 这将为 Cox 比例风险提供有用的替代方案 当比例风险假设不成立时的模式。