SREL Reprint #2727

Modeling uncertainty in the measurement of low-level analytes in environmental analysis

David M. Rocke1, Blythe Durbin1, Machelle Wilson1, and Henry D. Kahn2

1Department of Applied Science and Division of Biostatistics, University of California, Davis, CA 95616, USA
2US Environmental Protection Agency, USA

Abstract: The use of analytical chemistry measurements in environmental monitoring is dependent on an assessment of measurement error. Models for variation in measurements are needed to quantify uncertainty in measurements, set limits of detection, and preprocess data for more sophisticated analysis in prediction, classification, and clustering. This article explains how a two-component error model can be used to accomplish all of these objectives. In addition, we present applications to quantitating biomarkers of exposure to toxic substances using gene expression microarrays.

SREL Reprint #2727

Rocke, D. M., B. Durbin, M. Wilson, and H. D. Kahn. 2003. Modeling uncertainty in the measurement of low-level analytes in environmental analysis. Ecotoxicology and Environmental Safety 56:78-92.

This information was provided by the University of Georgia's Savannah River Ecology Laboratory (srel.uga.edu).