Flynn Michael R
Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, NC 27599-7431, USA.
Ann Occup Hyg. 2010 Apr;54(3):263-71. doi: 10.1093/annhyg/mep083. Epub 2009 Dec 2.
A new method for estimating the mean and standard deviation from censored exposure data is presented. The method W(MAX) treats the censored data as variables in a constrained optimization problem. Values for the censored data are calculated by maximizing the Shapiro-Wilk W statistic subject to the constraint that the values are between 0 and the limit of detection (or other censoring limit). The methodology is illustrated here with the Microsoft Excel Solver tool using real exposure data sets subject to repeated censoring. For the data sets explored here, the W(MAX) estimates are comparable to those obtained using the restricted maximum likelihood method based on bias as the performance index.
本文提出了一种从截尾暴露数据估计均值和标准差的新方法。W(MAX)方法将截尾数据视为约束优化问题中的变量。通过在值介于0和检测限（或其他截尾限）之间的约束条件下最大化夏皮罗-威尔克W统计量来计算截尾数据的值。本文使用Microsoft Excel求解器工具，通过实际暴露数据集并考虑重复截尾情况来说明该方法。对于此处探讨的数据集，以偏差作为性能指标，W(MAX)估计值与使用受限最大似然法获得的估计值相当。
