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Int. J. Environ. Res. Public Health 2015, 12(10), 12905-12923; doi:10.3390/ijerph121012905

A Case Study Perspective on Working with ProUCL and a State Environmental Agency in Determining Background Threshold Values

Applied Statistics, New Mexico State University, Department 3CQ, Post Office Box 30001, Las Cruces, NM 88003, USA
Academic Editor: Igor Burstyn
Received: 30 May 2015 / Revised: 5 October 2015 / Accepted: 12 October 2015 / Published: 15 October 2015
(This article belongs to the Special Issue Methodological Innovations and Reflections-1)
View Full-Text   |   Download PDF [891 KB, uploaded 15 October 2015]   |  

Abstract

ProUCL is a software package made available by the Environmental Protection Agency (EPA) to provide environmental scientists with better tools with which to conduct statistical analyses. ProUCL has been in production for over ten years and is in its fifth major version. In time, it has included more sophisticated and appropriate analysis tools. However, there is still substantial criticism of it among statisticians for its various omissions and even its philosophical approach. Due to limited resources, some state agencies have set ProUCL as a standard by which all state-mandated environmental analyses are compared, despite the EPA’s more open acceptance of other software products and methodologies. As such, it can be difficult for state-supervised sites to convince the state to allow the use of more appropriate methodologies or different software. In the current case study, several such instances arose and substantial resources were invested to demonstrate the appropriateness of alternative methodologies, sometimes without acquiring acceptance by the state despite sound statistical demonstration. In particular, efforts were made to address: inappropriate outlier detection, upper tolerance limit (UTL) calculations based on gamma distributions when non-detects were present, and inappropriate use of nonparametric UTL formulas. View Full-Text
Keywords: environmental monitoring; expectation maximization (EM) algorithm; gamma distribution; maximum order statistic; non-detect; nonparametric; outlier detection; ProUCL; regression on order statistics (ROS); upper tolerance limit (UTL) environmental monitoring; expectation maximization (EM) algorithm; gamma distribution; maximum order statistic; non-detect; nonparametric; outlier detection; ProUCL; regression on order statistics (ROS); upper tolerance limit (UTL)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Daniel, D.L. A Case Study Perspective on Working with ProUCL and a State Environmental Agency in Determining Background Threshold Values. Int. J. Environ. Res. Public Health 2015, 12, 12905-12923.

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