Linear regression with an independent variable subject to a detection limit.
Linear regression with an independent variable subject to a detection limit.
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DOI：
10.1097/ede.0b013e3181ce97d8
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发表时间：
2010-07
期刊：
影响因子：
--
通讯作者：
Schisterman EF
中科院分区：
文献类型：
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作者：
Nie L;Chu H;Liu C;Cole SR;Vexler A;Schisterman EF
最近，Richardson和Ciampi以及Schisterman和他的同事两组研究人员考虑了由于检测极限(LOD)而导致的带有左删失自变量X的线性回归。两组通过用一个常数替换左删失X得到了回归斜率的一致估计，即前一组中给定X低于LOD E(X|X<；LOD)的X的期望，而后者中给定X高于LOD的X的样本平均值。Schisterman和他的同事认为，他们的方法将是一个更好的选择，因为给定X的样本平均值高于LOD是可用的，而E(X|X<；LOD)是未知的。其他替换方法，例如用LOD或LOD/2替换左删失值，已经在文献中被广泛使用。通过仿真比较了自变量服从正态分布和非正态分布两种情况下的性能。在理论和仿真结果的基础上，给出了建议。这些建议通过1个案例研究进行了说明。
Linear regression with a left-censored independent variable X due to limit of detection (LOD) was recently considered by 2 groups of researchers: Richardson and Ciampi, and Schisterman and colleagues. Both groups obtained consistent estimators for the regression slopes by replacing left-censored X with a constant, that is, the expectation of X given X below LOD E(X|X<LOD) in the former group and the sample mean of X given X above LOD in the latter. Schisterman and colleagues argued that their approach would be a better choice because the sample mean of X given X above LOD is available, whereas E(X|X<LOD) is unknown. Other substitution methods, such as replacing the left-censored values with LOD, or LOD/2, have been extensively utilized in the literature. Simulations were conducted to compare the performance under 2 scenarios in which the independent variable is normally and not normally distributed. Recommendations are given based on theoretical and simulation results. These recommendations are illustrated with 1 case study.