生物医学研究中因检测范围所限致数据缺失时简单填补法对人口几何均数推断的影响（英文）  

The effect of simple imputation on inferences about population means when data are missing in biomedical research due to detection limits

作　　者：Hongyue WANG Guangqing CHEN Xiang LU Hui ZHANG Changyong FENG 

机构地区：[1]Departments of Biostatistics and Computational Biology, University of Rochester [2]Department of Biostatistics, St. Jude Children's Research Hospital [3]Department of Anesthesiology, University of Rochester

出　　处：《上海精神医学》2015年第5期319-325,共7页Shanghai Archives of Psychiatry

基　　金：supported by a pilot grant(PI:Feng)from the Clinical and Translational Sciences Institute at the University of Rochester Medical Center

摘　　要：概述:在生物医学和社会心理学研究中采用样本几何均值估计、比较人口几何均值的方法十分普遍。然而,由于测量工具的检测局限,有时无法观察到测量的实际值。处理这个问题的一种常见做法是用较小的正值常数来替代缺失值,然后在这些填补数据基础上进行统计推断。然而,这种简单的填补方法对推论的影响还没有研究过。我们在本文中阐明了这种简单的填补方法可能会大幅度地改变一项研究所报告的结果,因此即使检测限非常小,也会使结果难以解释。The sample geometric mean has been widely used in biomedical and psychosocial research to estimate and compare population geometric means. However, due to the detection limit of measurement instruments, the actual value of the measurement is not always observable. A common practice to deal with this problem is to replace missing values by small positive constants and make inferences based on the imputed data. However, no work has been carried out to study the effect of this nafve imputation method on inference, in this report, we show that this simple imputation method may dramatically change the reported outcomes of a study and, thus, make the results uninterpretable, even if the detection limit is very small.

关 键 词：生物医学 检测限 数据丢失 归责 几何平均值 原因 推论 测量仪器 

分 类 号：C912.6[经济管理] C924[社会学]