Estimation of Error and Bias in Bayesian Monte Carlo Decision Analysis Using the Bootstrap

Bayesian Monte Carlo (BMC) decision analysis adopts a sampling procedure to estimate likelihoods and distributions of outcomes, and then uses that information to calculate the expected performance of alternative strategies, the value of information, and the value of including uncertainty. These decision analysis outputs are therefore subject to sample error. The standard error of each estimate and its bias, if any, can be estimated by the bootstrap procedure. The bootstrap operates by resampling (with replacement) from the original BMC sample, and redoing the decision analysis. Repeating this procedure yields a distribution of decision analysis outputs. The bootstrap approach to estimating the effect of sample error upon BMC analysis is illustrated with a simple value-of-information calculation along with an analysis of a proposed control structure for Lake Erie. The examples show that the outputs of BMC decision analysis can have high levels of sample error and bias.     

Early identification of handicapped children: a time for social work involvement.

Early identification of handicapping conditions in children greatly enhances the possibility of treatment that may limit malfunctioning. Social work has responsibility and an opportunity to become more active in early identification.     

Rehabilitation Problems Amongst Aboriginals in North Australia

Physical, social and behavioural disabilities occur at a high rate amongst aboriginals. Probably no other group in Australia has a greater need for rehabilitation services. To date this need has been largely ignored. Token services have been provided in some places, usually in terms of european, middle class values. Greater recognition of the socioeconomic, cultural and related factors that influence rehabilitation activities and outcomes is needed if effective services to aboriginals are to be developed.     

Who Lives Near Coke Plants and Oil Refineries? An Exploration of the Environmental Inequity Hypothesis

Facility-specific information on pollution was obtained for 36 coke plants and 46 oil refineries in the United States and matched with information on populations surrounding these 82 facilities. These data were analyzed to determine whether environmental inequities were present, whether they were more economic or racial in nature, and whether the racial composition of nearby communities has changed significantly since plants began operations.The Census tracts near coke plants have a disproportionate share of poor and nonwhite residents. Multivariate analyses suggest that existing inequities are primarily economic in nature. The findings for oil refineries are not strongly supportive of the environmental inequity hypothesis. Rank ordering of facilities by race, poverty, and pollution produces limited (although not consistent) evidence that the more risky facilities tend to be operating in communities with above-median proportions of nonwhite residents (near coke plants) and Hispanic residents (near oil refineries). Over time, the racial makeup of many communities near facilities has changed significantly, particularly in the case of coke plants sited in the early 1900s. Further risk-oriented studies of multiple manufacturing facilities in various industrial sectors of the economy are recommended.The authors are all affiliated with the Harvard Center for Risk Analysis     

Risk analysis of PCB exposure via the soil-food crop pathway, and alternatives for remediation at Serpukhov, Russian Federation.

A risk assessment was conducted to determine the likelihood of certain health risks resulting from exposure to soils and food crops contaminated with polychlorinated biphenyl (PCBs). PCBs have contaminated soils, river sediments, and air in the past as a result of industrial activities at a capacitor plant located in the City of Serpukhov, Russian Federation. This risk assessment and suggestions for remediation are designed to aid in decision-making efforts by a joint Russian-American research team developing a community, national, and international response to industrial contamination. Bobovnikova et al. (The Science of the Total Environment 139/140, 357-364, [1993]) have reported that PCBs are elevated in soils and sediments, breast milk, and locally grown foods in the Serpukhov area. Data from these and other investigators have been used in this risk assessment to calculate a potential cancer risk resulting from exposure to PCBs. Our assessment indicates that members of the local population may be at increased risk of cancer, and possibly other adverse health effects, as a result of PCB contamination of their environment. Because previously unassessed environmental contamination is a common problem in the former Soviet Republics, as well as many other areas of the world, we believe this type of evaluation, using known methods, can serve as a model for assessment efforts in other parts of the globe and result in remediative efforts in regions constrained by faltering economies.