Correction for bias introduced by truncation in pharmacokinetics studies of environmental contaminants

Joel E. Michalek, Ram C. Tripathi, Pandurang M. Kulkarni, Pushpa L. Gupta, Kandansamy Selvavel

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

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 given an iterative estimation algorithm that produces this unbiased estimate with commercially available software for fitting a repeated measures linear model. The estimate and its efficacy 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.

Original languageEnglish (US)
Pages (from-to)165-174
Number of pages10
JournalEnvironmetrics
Volume9
Issue number2
StatePublished - Mar 1 1998
Externally publishedYes

Keywords

  • Biomarker
  • Decay rate
  • Least squares
  • Regression toward the mean

ASJC Scopus subject areas

  • Statistics and Probability
  • Ecological Modeling

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