Statistical methods for chronic disease research

描述(由申请人提供)：本研究的总体目标是 为几个重要和及时的问题开发新的统计方法 出现在癌症和艾滋病毒/艾滋病的临床研究中。将作出重大努力 走向(1)终生医疗成本分析，具有不完全的随访数据和 (2)Logistic回归和Cox回归中的协变量测量误差。当前 这两个领域的发展不充分，知识差距很大。 是存在的。在医学研究中，成本评估正在成为一个重要的组成部分 并已被整合到许多研究中，就像我们的医疗保健系统 有限的资源日益受到限制。然而，统计方法 对于终生医疗费用分析来说，随访数据不完整的情况下， 一直都很缺乏。这项工作将集中在开发半参数测试和 回归，它适应右审查的数据。第二个研究领域 关注回归协变量不准确的情况 可确定的，例如癌症预防研究中的饮食摄入量或CD4 HIV/AIDS研究中的淋巴细胞计数和病毒载量。参数-和 非参数校正方法将为广泛应用的Logistic方法开发 和考克斯回归与各种情况下的现有数据。尽管 这些长期存在的问题的挑战，初步调查 展示了优雅而实用的解决方案的相当大的前景。大样本 建议的测试统计量和估计器的属性将严格 利用标记点过程理论、鞅理论、 和现代经验过程理论。将进行广泛的模拟研究 在实际样本量下对这些建议进行验证。这个 建议的方法将应用于一些癌症和艾滋病毒/艾滋病的临床 审判。将开发用户友好的计算机程序并提供给 研究界。

DESCRIPTION (provided by applicant): The broad objective of this research is to develop new statistical methods for several important and timely problems that arise in cancer and HIV/AIDS clinical research. Major efforts will be directed toward (1) lifetime medical cost analysis with incomplete follow-up data and (2) covariate measurement error in logistic and Cox regressions. Current development in these two areas is inadequate and substantial gaps of knowledge exist. In medical research cost evaluation is becoming an important component and has been integrated in many studies, as our health care system is increasingly constrained with limited resources. However, statistical methods for lifetime medical cost analysis with incomplete follow-up data have largely been lacking. This work will focus on developing semipararametric tests and regressions, which accommodate right-censored data. The second area of research concerns the situation that regression covariates are not accurately ascertainable, e.g. dietary intakes in cancer prevention studies or CD4 lymphocyte count and viral load in HIV/AIDS research. Parametric- and nonparametric-correction methods will be developed for widely-applied logistic and Cox regressions with various scenarios of available data. Despite the challenges of these long-standing problems, preliminary investigations have shown considerable promise for elegant and practical solutions. Large-sample properties of the proposed test statistics and estimators will be rigorously investigated by making use of marked point process theory, martingale theory, and modern empirical process theory. Extensive simulation studies will be performed to validate these proposals under practical sample sizes. The proposed methods will be applied to a number of cancer and HIV/AIDS clinical trials. User-friendly computer programs will be developed and made available to the research community.