非参数风险函数界。
Nonparametric Bounds for the Risk Function.
机构信息
Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina.
Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina.
出版信息
Am J Epidemiol. 2019 Apr 1;188(4):632-636. doi: 10.1093/aje/kwz013.
Abstract
Nonparametric bounds for the risk difference are straightforward to calculate and make no untestable assumptions about unmeasured confounding or selection bias due to missing data (e.g., dropout). These bounds are often wide and communicate uncertainty due to possible systemic errors. An illustrative example is provided.
摘要
非参数风险差界容易计算，并且由于缺失数据（例如辍学）不会对未测量的混杂或选择偏差做出未经检验的假设。这些界通常很宽，并由于可能存在系统性错误而传达不确定性。提供了一个说明性示例。
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J Am Stat Assoc. 2018;113(522):933-947. doi: 10.1080/01621459.2018.1434530. Epub 2018 Jul 25.
2
Cohort Profile: The Women's Interagency HIV Study (WIHS).队列简介：妇女机构间HIV研究（WIHS）
Int J Epidemiol. 2018 Apr 1;47(2):393-394i. doi: 10.1093/ije/dyy021.
3
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