Comparing Model Averaging with Other Model Selection Strategies for Benchmark Dose Estimation

Details

• Personal Author:
  Bailer AJ ; Wheeler, Matthew W.
• Description:
  Model averaging (MA) has been proposed as a method of accommodating model uncertainty when estimating risk. Although the use of MA is inherently appealing, little is known about its performance using general modeling conditions. We investigate the use of MA for estimating excess risk using a Monte Carlo simulation. Dichotomous response data are simulated under various assumed underlying dose-response curves, and nine dose-response models (from the USEPA Benchmark dose model suite) are fit to obtain both model specific and MA risk estimates. The benchmark dose estimates (BMDs) from the MA method, as well as estimates from other commonly selected models, e.g., best fitting model or the model resulting in the smallest BMD, are compared to the true benchmark dose value to better understand both bias and coverage behavior in the estimation procedure. The MA method has a small bias when estimating the BMD that is similar to the bias of BMD estimates derived from the assumed model. Further, when a broader range of models are included in the family of models considered in the MA process, the lower bound estimate provided coverage close to the nominal level, which is superior to the other strategies considered. This approach provides an alternative method for risk managers to estimate risk while incorporating model uncertainty. [Description provided by NIOSH]
• Subjects:
  Occupational Health Risk Assessment Safety
• Keywords:
  Author Keywords: Bayesian Model Averaging Dose-response Mathematical-models Measurement-equipment Model Uncertainty Risk-analysis Risk Estimation Statistical-analysis Statistical-quality-control
• ISSN:
  1352-8505
• Document Type:
  Text
• Genre:
  Journal Article
• Place as Subject:
  Ohio ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  EID - Education and Information Division
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  37-51
• Volume:
  16
• Issue:
  1
• NIOSHTIC Number:
  nn:20035046
• Citation:
  Environ Ecol Stat 2009 Mar; 16(1):37-51
• Contact Point Address:
  Matthew W. Wheeler, CDC, National Institute for Occupational Safety and Health, MS C-15, 4676 Columbia Parkway, Cincinnati, OH 45226
• Email:
  aez0@cdc.gov
• Federal Fiscal Year:
  2009
• Peer Reviewed:
  True
• Source Full Name:
  Environmental and Ecological Statistics
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:559fb5a72964b9a59eaf243580955a07dac2f0f3972a45018cb2396a423c941094350fe403ab7fcc6be391225a03cfe0e2638c63077283ca8bfc64fc5d6d15e7
• Download URL:
  https://stacks.cdc.gov/view/cdc/187032/cdc_187032_DS1.pdf
• File Type:
  [PDF - 525.30 KB ]