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Applied and Environmental Microbiology, May 2006, p. 3468-3475, Vol. 72, No. 5
0099-2240/06/$08.00+0     doi:10.1128/AEM.72.5.3468-3475.2006
Copyright © 2006, American Society for Microbiology. All Rights Reserved.

Classification Tree Method for Bacterial Source Tracking with Antibiotic Resistance Analysis Data

Bertram Price,1* Elichia A. Venso,2,3 Mark F. Frana,2 Joshua Greenberg,1 Adam Ware,1 and Lee Currey4

Price Associates, One North Broadway, White Plains, New York 10601,1 Department of Biological Sciences,2 Environmental Health Science, Salisbury University, Salisbury, Maryland 21801,3 Maryland Department of the Environment, 1800 Washington Blvd., Baltimore, Maryland 21230-17184

Received 11 October 2005/ Accepted 27 February 2006

Various statistical classification methods, including discriminant analysis, logistic regression, and cluster analysis, have been used with antibiotic resistance analysis (ARA) data to construct models for bacterial source tracking (BST). We applied the statistical method known as classification trees to build a model for BST for the Anacostia Watershed in Maryland. Classification trees have more flexibility than other statistical classification approaches based on standard statistical methods to accommodate complex interactions among ARA variables. This article describes the use of classification trees for BST and includes discussion of its principal parameters and features. Anacostia Watershed ARA data are used to illustrate the application of classification trees, and we report the BST results for the watershed.

* Corresponding author. Mailing address: Price Associates, One North Broadway, White Plains, NY 10601. Phone: (914) 686-7975. Fax: (914) 686-7977. E-mail: bprice{at}priceassociatesinc.com.

Applied and Environmental Microbiology, May 2006, p. 3468-3475, Vol. 72, No. 5
0099-2240/06/$08.00+0     doi:10.1128/AEM.72.5.3468-3475.2006
Copyright © 2006, American Society for Microbiology. All Rights Reserved.





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