Statistics Papers

Document Type

Journal Article

Date of this Version

10-2015

Publication Source

Statistics in Biosciences

Volume

7

Issue

2

Start Page

206

Last Page

224

DOI

10.1007/s12561-014-9113-5

Abstract

The standard methods of diagnosing disease based on antibody microtiter plates are quite crude. Few methods create a rigorous underlying model for the antibody levels of populations consisting of a mixture of positive and negative subjects, and fewer make full use of the entirety of the available data for diagnoses. In this paper, we propose a Bayesian hierarchical model that provides a systematic way of pooling data across different plates, and accounts for the subtle sources of variations that occur in the optical densities of typical microtiter data. In addition to our Bayesian method having good frequentist properties, we find that our method outperforms one of the standard crude approaches (the “3SD Rule”) under reasonable assumptions, and provides more accurate disease diagnoses in terms of both sensitivity and specificity.

Copyright/Permission Statement

The final publication is available at Springer via http://dx.doi.org/10.1007/s12561-014-9113-5.

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Date Posted: 27 November 2017

This document has been peer reviewed.