title: Method for analyzing left-censored bioassay data in large cohort studies.
abstract: In retrospective epidemiological studies of large cohorts of workers exposed to radioactive materials, it is often necessary to analyze large numbers of bioassay data sets containing censored values, or values recorded as less than a detection limit. Censored bioassay data create problems for all bioassay analysis methods, including analytical techniques based on least-squares regression to estimate intakes. A method is presented here that uses a simple empirically-derived equation for imputing replacement values for urine uranium concentration results reported as zero or less than a detection limit, that produces minimal bias in intakes estimated using least-square regression methods with the assumption of lognormally distributed measurement errors.
authors.affiliation: Division of Surveillance, Hazard Evaluations and Field Studies (DSHEFS), National Institute for Occupational Safety and Health (NIOSH), Cincinnati, Ohio, USA.
authors.forename: Jeri L
authors.initials: JL
authors.lastname: Anderson
authors.affiliation: Oak Ridge Center for Risk Analysis, Oak Ridge, Tennessee, USA.
authors.forename: A Iulian
authors.initials: AI
authors.lastname: Apostoaei
mesh_terms: D015982:Bias; D001681:Biological Assay; D015331:Cohort Studies; D003198:Computer Simulation; D004784:Environmental Monitoring / Q000379:methods; D006801:Humans; D009010:Monte Carlo Method; D009314:National Institute for Occupational Safety and Health, U.S.; D016273:Occupational Exposure / Q000032:analysis*; D012044:Regression Analysis; D014481:United States; D014501:Uranium / Q000652:urine*
chemical_list: D014501:Uranium