Change-point models to estimate the limit of detection

Ryan C. May, Haitao Chu, Joseph G. Ibrahim, Michael G. Hudgens, Abigail C. Lees, David M. Margolis

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)4995-5007
Number of pages13
JournalStatistics in Medicine
Volume32
Issue number28
DOIs
StatePublished - Dec 10 2013

Bibliographical note

Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.

Keywords

  • Change point
  • Limit of detection
  • Linear calibration curve
  • Two-stage maximum likelihood

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