BOHS Professional Development Course - Bayesian Statistics - Overview and Applications in Sampling Data Interpretation and Exposure Risk Assessment

Start time: 09:00
Finish time: 17:00  

The Bayesian statistical framework offers exciting opportunities for improving the accuracy, efficiency and transparency of our exposure judgements. Bayesian techniques can be used to formally combine our professional judgement regarding a particular exposure and its uncertainty, along with the statistical analysis of current exposure data. The language and framework of the approach holds promise for expressing the output of exposure assessments in a manner that is much more easily understood and communicated than the output from more traditional statistical analysis. Best of all, the Bayesian decision analysis approach formalizes traditional exposure assessment processes already used by OHs today.

This course will provide an overview of the Bayesian framework for decision analysis and will explore, through discussion and workshops, opportunities for its application in IH data interpretation and exposure-risk assessment. A software program for performing Bayesian decision analysis calculations will be distributed. Note that the software is designed for Windows-based PCs. It will not run on a Macintosh computer without an emulator.  This course will likely give you skills to impress your friends, family members and/or co-workers.  Depending on your engagement and understanding during the course, you may become more attractive and popular regardless of your current statistical skills. 

Outline:

• A comprehensive exposure assessment model: Inherently, a Bayesian approach 

• Exposure assessment (EA) model integration of qualitative, semi-qualitative and quantitative EA techniques 

• Importance of professional judgement 

• Performance based EA strategies and Bayesian decision analysis 

• Brief review of traditional IH statistics 

• Bayesian decision analysis tool overview and workshops 

• Basic monitoring data analysis: Bayesian likelihood 

• Advanced monitoring data analysis: Incorporating qualitative assessments 

• Bayesian decision analysis: Caveats, cautions and conundrums 

 

Outcomes: Upon completion participants will be able to:

• Describe a Bayesian framework for decision analysis 

• Discuss a Bayesian framework for decision analysis and common exposure assessment strategies 

• Through a course workshop in the course, each participant should be able to utilise Bayesian decision tools to the implementation of a performance-based exposure risk assessment strategy 

• Use software to perform a Bayesian decision analysis of exposure monitoring data 
   

Instructors: Paul Hewitt PhD CIH, Exposure Assessment Solutions, Morgantown, WV
Perry Logan PhD CIH 3M Company, St. Paul, MN

Prerequisites: Familiarity with strategies for assessing and managing occupational exposures. Experience in exposure assessments and monitoring data interpretation.

Learning aids: Participants must bring a laptop computer (PCs only, no Macs). Several powerful freeware packages and positive encouragement will be given out during the course.

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