Basic and Applied Statistical Inference and Measurement

在过去二十年中，统计数据和推断在确定用于确定公共政策的基本事实方面发挥了越来越大的作用，例如，估计艾滋病毒感染的流行程度，评估职业或环境暴露导致的癌症风险，评估收入分配和法律环境的变化，特别是在涉及就业歧视和学校隔离的案件中。该项目的目的是研究在这些情况下产生的统计问题，并为解决这些问题制订适当的概率模型和统计方法。强调了当几个科学上似是而非的模型可能是数据的基础或少数观察结果可能是错误的时候，导致统计上有效推论的可靠方法。将开发不同的方法来评估遗漏因素和测量误差对从其他有效研究中得出的推论的潜在影响。这一项目的完成应确立群体测试在人口或劳动力中某种特征（如艾滋病毒）的识别、质量控制和保密估计方面的适用性。该项目的第二项任务，即开发评估调查中遗漏因素和错误分类造成的统计偏差的方法，如果成功完成，可能对法律和公共政策制定产生非常重要的影响，因为法院声称，即使一个错误也可以证明对统计研究的批评是合理的。首席研究员已经在统一不同应用领域使用的方法和评估从研究中得出的结论的可能错误的严重性方面取得了重大进展。

During the last twenty years statistical data and inference have played an increasing role in establishing basic facts used in determining public policy, e.g., estimating the prevalence of HIV infection, evaluating the risk of cancer from occupational or environmental exposures, assessing changes in the income distribution and in the legal environmental setting, especially in cases concerning employment discrimination and school segregation. The purpose of the project is to study statistical problems arising in these contexts and to develop appropriate probability models and statistical methodology for their solution. Robust methods which lead to statistically valid inferences when several scientifically plausible models may underlie the data or when a few observations may be erroneous are emphasized. Different approaches for assessing the potential effect of an omitted factor and measurement errors on inferences drawn from otherwise valid studies will be developed. The completion of this project should establish the applicability of group testing to the identification, quality control and confidential estimation of the prevalence of a trait (such as the HIV virus) in a population or workforce. The successful completion of the second task of the project, namely, the development of methods for assessing the statistical bias resulting from omitted factors and misclassification in surveys, could have a very important impact in the legal and public policy setting as courts have claimed that even one error can justify criticism of a statistical study. The principal investigator has already made significant progress in unifying approaches used in various areas of application and in assessing the seriousness of the possible error on the conclusions drawn from a study.