Using relative utility curves to evaluate risk prediction

Summary.  Because many medical decisions are based on risk prediction models that are constructed from medical history and results of tests, the evaluation of these prediction models is important. This paper makes five contributions to this evaluation: the relative utility curve which gauges the potential for better prediction in terms of utilities, without the need for a reference level for one utility, while providing a sensitivity analysis for misspecification of utilities, the relevant region, which is the set of values of prediction performance that are consistent with the recommended treatment status in the absence of prediction, the test threshold, which is the minimum number of tests that would be traded for a true positive prediction in order for the expected utility to be non-negative, the evaluation of two-stage predictions that reduce test costs and connections between various measures of performance of prediction. An application involving the risk of cardiovascular disease is discussed.     

Automating and evaluating reversible jump MCMC proposal distributions

The reversible jump Markov chain Monte Carlo (MCMC) sampler (Green in Biometrika 82:711–732, 1995) has become an invaluable device for Bayesian practitioners. However, the primary difficulty with the sampler lies with the efficient construction of transitions between competing models of possibly differing dimensionality and interpretation. We propose the use of a marginal density estimator to construct between-model proposal distributions. This provides both a step towards black-box simulation for reversible jump samplers, and a tool to examine the utility of common between-model mapping strategies. We compare the performance of our approach to well established alternatives in both time series and mixture model examples.     

Microforms

Abstract

The editors scan approximately 140 journals in all disciplines for reviews of serial publications. Journals published since January 2000 were monitored for this installment of Serials Review Index. Suggestions for journals to be included in future columns are welcome. Serials Review 2002; 28:57–62.     

Risk,Media, and Stigma at Rocky Flats

Public responses to nuclear technologies are often strongly negative. Events, such as accidents or evidence of unsafe conditions at nuclear facilities, receive extensive and dramatic coverage by the news media. These news stories affect public perceptions of nuclear risks and the geographic areas near nuclear facilities. One result of these perceptions, avoidance behavior, is a form of technological stigma that leads to losses in property values near nuclear facilities. The social amplification of risk is a conceptual framework that attempts to explain how stigma is created through media transmission of information about hazardous places and public perceptions and decisions. This paper examines stigma associated with the U.S. Department of Energy's Rocky Flats facility, a major production plant in the nation's nuclear weapons complex, located near Denver, Colorado. This study, based upon newspaper analyses and a survey of Denver area residents, finds that the social amplification theory provides a reasonable framework for understanding the events and public responses that took place in regard to Rocky Flats during a 6-year period, beginning with an FBI raid of the facility in 1989.