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Change‐point models to estimate the limit of detection
Authors:Ryan C May  Haitao Chu  Joseph G Ibrahim  Michael G Hudgens  Abigail C Lees  David M Margolis
Institution:1. The EMMES Corporation, , Rockville, Maryland 20850, U.S.A.;2. Division of Biostatistics, School of Public Health, University of Minnesota, , Minneapolis, Minnesota 55455, U.S.A.;3. Department of Biostatistics, University of North Carolina at Chapel Hill, , Chapel Hill, North Carolina 27599, U.S.A.;4. Division of Infectious Diseases, Department of Medicine, University of North Carolina at Chapel Hill, , Chapel Hill, North Carolina 27599, U.S.A.;5. Department of Medicine, Epidemiology, Microbiology and Immunology, University of North Carolina at Chapel Hill, , Chapel Hill, North Carolina 27599, U.S.A.
Abstract:In many biological and environmental studies, measured data is subject to a limit of detection. The limit of detection is generally defined as the lowest concentration of analyte that can be differentiated from a blank sample with some certainty. Data falling below the limit of detection is left censored, falling below a level that is easily quantified by a measuring device. A great deal of interest lies in estimating the limit of detection for a particular measurement device. In this paper, we propose a change‐point model to estimate the limit of detection by using data from an experiment with known analyte concentrations. Estimation of the limit of detection proceeds by a two‐stage maximum likelihood method. Extensions are considered that allow for censored measurements and data from multiple experiments. A simulation study is conducted demonstrating that in some settings the change‐point model provides less biased estimates of the limit of detection than conventional methods. The proposed method is then applied to data from an HIV pilot study. Copyright © 2013 John Wiley & Sons, Ltd.
Keywords:change point  limit of detection  linear calibration curve  two‐stage maximum likelihood
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