Determining how detailed risk analysis models should be is an important question in analyzing the risks of complex technological systems such as nuclear power plants, liquid natural gas storage facilities, hazardous material transport, and the space shuttle. Both overly detailed and overly simplistic models can lead to erroneous risk estimates. However, this issue has gone virtually unstudied despite the widespread growth of risk analysis in the last 15 years. Past work by one of the investigators on this project has identified three potential sources of error in risk analyses: modeling error; parameter error; and aggregation error. Different types of errors are minimized by simple versus detailed models. In particular, in the case of aggregation error, the use of overly simple models can neglect information that may be available at more detailed levels. For example, at the time of the Challenger disaster, an aggregate analysis based only on 0 accidents in 23 flights would have indicated increasing reliability with each flight. However, a disaggregate analysis including the evidence of O-ring erosion on 6 of the 23 flights would have concluded that a substantial level of risk remained. The principal investigators for this project have identified necessary and sufficient conditions for aggregation error to vanish in simple risk analysis models. However, these conditions are unlikely to be achieved in practice. Therefore, there is a need to understand the determinants of aggregation error when perfect aggregation is not achieved. The proposed work will provide guidance on the circumstances under which aggregation error will be severe, so that large errors can be avoided through the use of more detailed models in such cases.
