Linear regression with an independent variable subject to a detection limit

Lei Nie, Haitao Chu, Chenglong Liu, Stephen R. Cole, Albert Vexler, Enrique F. Schisterman

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)S17-S24
JournalEpidemiology
Volume21
Issue numberSUPPL. 4
DOIs
StatePublished - Jul 2010

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