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 an innovative change-point model to estimate the limit of detection using data from an experiment with known analyte concentrations. Estimation of the limit of detection proceeds by way of a two-stage maximum likelihood method. The proposed methodology is analyzed via simulation, and is applied to copy number data from an HIV pilot study. This method is shown to lead to improved estimation of the limit of detection.

Keywords: Change Point; Linear Calibration Curve; Limit of Detection; Two-Stage Maximum Likelihood



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