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doi: 10.1097/EDE.0b013e3181ce97d8
Methodologic Issues in Environmental Exposures: Mixtures and Limits of Detection: Original Article

Linear Regression With an Independent Variable Subject to a Detection Limit

Nie, Leia; Chu, Haitaob; Liu, Chenglongc; Cole, Stephen R.d; Vexler, Alberte; Schisterman, Enrique F.f

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Background: 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 (Am J Epidemiol. 2003;157:355-363), and Schisterman et al (Am J Epidemiol. 2006;163:374-383).

Methods: 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.

Results: Schisterman et al 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 used in the literature. Simulations were conducted to compare the performance under 2 scenarios in which the independent variable is normally and not normally distributed.

Conclusion: Recommendations are given based on theoretical and simulation results. These recommendations are illustrated with one case study.

© 2010 Lippincott Williams & Wilkins, Inc.

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