<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Matzke, Melissa M</style></author><author><style face="normal" font="default" size="100%">Sarah E Allan</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author><author><style face="normal" font="default" size="100%">Katrina M Waters</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An approach for calculating a confidence interval from a single aquatic sample for monitoring hydrophobic organic contaminants.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Toxicol Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Toxicol. Chem.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Confidence Intervals</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Hydrophobic and Hydrophilic Interactions</style></keyword><keyword><style  face="normal" font="default" size="100%">Pilot Projects</style></keyword><keyword><style  face="normal" font="default" size="100%">Polycyclic Hydrocarbons, Aromatic</style></keyword><keyword><style  face="normal" font="default" size="100%">Water Pollutants, Chemical</style></keyword><keyword><style  face="normal" font="default" size="100%">Water Pollution, Chemical</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2012</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">2888-92</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The use of passive sampling devices (PSDs) for monitoring hydrophobic organic contaminants in aquatic environments can entail logistical constraints that often limit a comprehensive statistical sampling plan, thus resulting in a restricted number of samples. The present study demonstrates an approach for using the results of a pilot study designed to estimate sampling variability, which in turn can be used as variance estimates for confidence intervals for future n = 1 PSD samples of the same aquatic system. Sets of three to five PSDs were deployed in the Portland Harbor Superfund site for three sampling periods over the course of two years. The PSD filters were extracted and, as a composite sample, analyzed for 33 polycyclic aromatic hydrocarbon compounds. The between-sample and within-sample variances were calculated to characterize sources of variability in the environment and sampling methodology. A method for calculating a statistically reliable and defensible confidence interval for the mean of a single aquatic passive sampler observation (i.e., n = 1) using an estimate of sample variance derived from a pilot study is presented. Coverage probabilities are explored over a range of variance values using a Monte Carlo simulation.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/22997050?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kevin A Hobbie</style></author><author><style face="normal" font="default" size="100%">Elena S Peterson</style></author><author><style face="normal" font="default" size="100%">Michael L Barton</style></author><author><style face="normal" font="default" size="100%">Katrina M Waters</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integration of data systems and technology improves research and collaboration for a superfund research center.</style></title><secondary-title><style face="normal" font="default" size="100%">J Lab Autom</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Lab Autom</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biostatistics</style></keyword><keyword><style  face="normal" font="default" size="100%">Chemistry Techniques, Analytical</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Cooperative Behavior</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Health</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Integrated Advanced Information Management Systems</style></keyword><keyword><style  face="normal" font="default" size="100%">Oregon</style></keyword><keyword><style  face="normal" font="default" size="100%">Polycyclic Hydrocarbons, Aromatic</style></keyword><keyword><style  face="normal" font="default" size="100%">Universities</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2012</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">275-83</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Large collaborative centers are a common model for accomplishing integrated environmental health research. These centers often include various types of scientific domains (e.g., chemistry, biology, bioinformatics) that are integrated to solve some of the nation&#039;s key economic or public health concerns. The Superfund Research Center (SRP) at Oregon State University (OSU) is one such center established in 2008 to study the emerging health risks of polycyclic aromatic hydrocarbons while using new technologies both in the field and laboratory. With outside collaboration at remote institutions, success for the center as a whole depends on the ability to effectively integrate data across all research projects and support cores. Therefore, the OSU SRP center developed a system that integrates environmental monitoring data with analytical chemistry data and downstream bioinformatics and statistics to enable complete &quot;source-to-outcome&quot; data modeling and information management. This article describes the development of this integrated information management system that includes commercial software for operational laboratory management and sample management in addition to open-source custom-built software for bioinformatics and experimental data management.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">&lt;p&gt;http://www.ncbi.nlm.nih.gov/pubmed/22651935?dopt=Abstract&lt;/p&gt;
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