PDC 425

Bayesian Statistics: Applications in IH Data Interpretation

intermediate | 8 CM Credit Hours / 0.8 CEU/COC / 0.5 CMP
Sunday | 8:00 A.M. – 5:00 P.M.
Limit: 60

Topic:
Exposure Assessment Strategies

JUST 10 SEATS REMAINING!

Description:

The Bayesian statistical framework offers exciting opportunities for improving the accuracy, efficiency, and transparency of our exposure judgments. Bayesian techniques can be used to formally combine our professional judgment 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 industrial hygienists today. This PDC will provide an overview of the Bayesian framework for decision analysis and explore, through discussion and workshops, opportunities for its application in IH data interpretation and exposure risk assessment.

Value Added:

Software used to perform Bayesian decision analysis calculations will be distributed and used to improve exposure judgments.

Prerequisites:

Familiar with the AIHA® Strategy for Assessing and Managing Occupational Exposures. Experienced in exposure assessments and monitoring data interpretation.

Learning Aids:

Attendees should bring a laptop for the Bayesian decision analysis software that will be distributed. Note that the software is designed for a Windows-based PC. It will not run on a Mac without an emulator.

Outcomes:

Upon completion, participants will be able to

  • Implement techniques for improving the accuracy of their exposure judgments.
  • Relate a Bayesian framework for decision analysis to the AIHA Exposure Assessment Strategy.
  • Use a software tool to perform Bayesian decision analysis of IH monitoring data.

Outline:

  • Making Good Exposure Decisions: Interpreting Data
  • Importance of Professional Judgment
  • AIHA Exposure Assessment Model: Inherently a Bayesian Approach
  • Improving Judgments: Bayesian Decision Analysis (BDA) Theory and Tool
  • Putting Improvement Ideas to Practice: Scenario Examples
  • Use of Subjective Decisions
  • Integrating Improvement Activities into Your Professional Practice

Transfer of Knowledge:

Instructors will evaluate participants understanding of the materials presented based on

  • Practice exercises,
  • Workshops, and
  • Group activities.

Sponsoring Committee: Exposure Assessment Strategies

ONLINE COURSE EVALUATION: https://www.surveymonkey.com/s/PGDPC7K

Instructors: