Change-point models to estimate the limit of detection.

Publication Type
Journal Article
Year of Publication
May, Ryan C; Chu, Haitao; Ibrahim, Joseph G; Hudgens, Michael G; Lees, Abigail C; Margolis, David M
Stat Med
Date Published
2013 Dec 10
Computer Simulation; HIV; HIV Infections; Humans; Likelihood Functions; limit of detection; Models, Statistical; Real-Time Polymerase Chain Reaction; RNA, Viral

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.