Electronic Resource
350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK .
:
Blackwell Publishing, Inc.
Risk analysis
25 (2005), S. 0
ISSN:
1539-6924
Source:
Blackwell Publishing Journal Backfiles 1879-2005
Topics:
Energy, Environment Protection, Nuclear Power Engineering
Notes:
Experimental animal studies often serve as the basis for predicting risk of adverse responses in humans exposed to occupational hazards. A statistical model is applied to exposure-response data and this fitted model may be used to obtain estimates of the exposure associated with a specified level of adverse response. Unfortunately, a number of different statistical models are candidates for fitting the data and may result in wide ranging estimates of risk. Bayesian model averaging (BMA) offers a strategy for addressing uncertainty in the selection of statistical models when generating risk estimates. This strategy is illustrated with two examples: applying the multistage model to cancer responses and a second example where different quantal models are fit to kidney lesion data. BMA provides excess risk estimates or benchmark dose estimates that reflects model uncertainty.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1111/j.1539-6924.2005.00590.x
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