Abstract Details
Activity Number:
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652
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Type:
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Contributed
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Date/Time:
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Thursday, August 7, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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Abstract #312017
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Title:
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Poisson Regression Models for Safety Analysis
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Author(s):
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Rama Sastry*+
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Companies:
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Keywords:
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Poisson ;
Models
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Abstract:
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M. Rama Sastry Ph.D., United States Department of Energy (DOE) and the School of Public Health, George Washington University, Washington, DC Somak Chatterjee, Department of Statistics, The George Washington University, Washington, DC
The objective of the study is to illustrate the potential use of the statistical methods, when analyzing safety data. In accordance with OSHA 29 CFR, and other Health and Safety requirements and standards, DOE maintains large sets of data on information concerning near misses and injury illness rates etc. as reported by major contractors. DOE is responsible for oversight and protecting public and contract worker safety at various facilities located throughout the United Sates. Examples of facilities include National Laboratories located in Oak Ridge, Brookhaven, Los Alamos, and sites where extensive environmental remediation and cleanup activities are conducted. Select research data were obtained from publically available DOE sources, and statistical models such as Poisson Regression, were used to analyze the data. This research was conducted at the George Washington University using SAS Version 9.1.
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Authors who are presenting talks have a * after their name.
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