Basic and Applied Statistical Inference and Measurement

在过去的二十年里，统计数据和推断 在确定用于以下方面的基本事实方面发挥了越来越大的作用： 确定公共政策，例如， 估计艾滋病毒流行率 感染，评估职业或 环境风险，评估收入变化 分布和法律的环境设置，特别是 在涉及就业歧视和学校歧视的案件中， 种族隔离 该项目的目的是研究统计 在这些情况下出现的问题，并制定适当的 概率模型和统计方法的解决方案。 鲁棒的方法，导致统计上有效的推论， 几个科学上合理的模型可能是数据的基础， 当一些观察可能是错误的，强调。 不同 评估遗漏因素潜在影响的方法 和测量误差的推断得出，否则有效 将开展研究。 该项目完成后， 群体检验对鉴定、质量 控制和机密估计一个特征的流行 (such艾滋病病毒）在人口或劳动力中。 的 圆满完成项目的第二项任务，即： 制定评估统计偏倚的方法 由于调查中遗漏的因素和错误的分类， 可能会对法律的和公共政策产生重要影响 法院声称，即使是一个错误， 对一项统计研究的批评。 主要研究者 已经在统一 在各种应用领域和评估 从一项研究中得出的结论可能存在的错误。

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.