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Correction for bias introduced by truncation in pharmacokinetic studies of environmental contaminants
Author(s) -
Michalek Joel E.,
Tripathi Ram C.,
Kulkarni Pandurang M.,
Gupta Pushpa L.,
Selvavel Kandansamy
Publication year - 1998
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/(sici)1099-095x(199803/04)9:2<165::aid-env293>3.0.co;2-6
Subject(s) - truncation (statistics) , statistics , context (archaeology) , mathematics , population , least squares function approximation , econometrics , medicine , environmental health , biology , paleontology , estimator
Pharmacokinetic studies of biomarkers for environmental contaminants in humans are generally restricted to a few measurements per subject taken after the initial exposure. Subjects are selected for inclusion in the study if their measured body burden is above a threshold determined by the distribution of the biomarker in a control population. Such selection procedures introduce bias in the ordinary weighted least squares estimate of the decay rate λ caused by the truncation. We show that if the data are conditioned to lie above a line with slope −λ on the log scale then the weighted least squares estimate of λ is unbiased. We give an iterative estimation algorithm that produces this unbiased estimate with commercially available software for fitting a repeated measures linear model. The estimate and its efficiency are discussed in the context of a pharmacokinetic study of 2,3,7,8‐tetrachlorodibenzo‐ p ‐dioxin. Unbiasedness and efficiency are demonstrated with a simulation. © 1998 John Wiley & Sons, Ltd.