ESTIMATING THE COMMON MEAN OF A BIVARIATE NORMAL POPULATION

For estimating the common mean of a bivariate normal distribution, Krishnamoorthy & Rohatgi (1989) proposed some estimators which dominate the maximum likelihood estimator in a large region of the parameter space. We consider some modifications of these estimators and study their risk performance.     

Eliciting and Classifying Concerns: A Methodological Critique

Two methodological steps in the study of peoples'concerns are elicitation and classification. Elicitation of concerns through analytical methods such as surveys can be supplemented with techniques that perform more diversively. We present two examples of how this can be accomplished: one in the expert community and one in the lay community. A classification taxonomy is a subjective choice of the researcher and it can only be evaluated against the stated objectives of the research. We present a classification schema that is explicitly oriented toward diagnosing the substantive needs of public discourses about risk decision making. To illustrate how concerns can be elicited in a social setting and how this classification tool can be applied, we report on a public participation exercise in New Jersey where citizens discussed the impacts of land application of sewage sludge at an experimental farm.     

Characterising the Perceived Risks and Benefits of Some Health Issues

Previous work on perceived risk, particularly a study by Fischhoff et al. (1978), is critically examined with reference to its applicability to specific health related issues. Judgments were obtained from 159 subjects of 15 health-related items in terms of perceived risk, benefit, and a number of risk characteristics based on the Fischhoff et al. research. In addition, demographic details concerning sex of respondent, seat belt usage, smoking status, and birth order were collected. Using regression analyses it was found that the direction of the risk-benefit relationship was dependent on the issue being judged. Risk was found to be better explained by ratings of likelihood of mishap and likelihood of death as a consequence of mishap. Benefit was poorly explained by the risk characteristics and demographic data. However, subject group characteristics were shown to be important influences on risk and benefit perception in certain situations. The implications of these results for understanding behavioral decisions involving risk in relation to specific activities are discussed.     

Probabilistic Risk Analyses: NRC Programs and Perspectives

The historical basis and more recent activities and products of probabilistic risk analysis (PRA) in the Atomic Energy Commission and Nuclear Regulatory Commission (NRC) are reviewed. Current NRC program activities and objectives are described. The author's opinions on the best uses of PRA are presented.     

Using the Biological Two-Stage Model to Assess Risk from Short-Term Exposures

Two assumptions used in risk assessment are investigated: (1) the assumption of fraction of lifetime dose rate assumes that the risk from a fractional lifetime exposure at a given dose rate is equal to the risk from full lifetime exposure at that same fraction of the given dose rate; (2) the assumption of fraction of lifetime risk assumes that the risk from a fractional lifetime exposure at a given dose rate is equal to that same fraction of the risk from full lifetime exposure at the same dose rate. These two assumptions are equivalent when risk is a linear function of dose. Thus both can be thought of as generalizations of the assumption that cancer risk is proportional to the total accumulated lifetime dose (or average daily dose), which is often made to assess the risk from short-term exposures. In this paper, the age-specific cumulative hazard functions are derived using the two-stage model developed by Moolgavkar, Venzon, and Knudson for situations when the exposure occurs during a single period or a single instant. The two assumptions described above are examined for three types of carcinogens, initiator, completer, and promoter, in the context of the model. For initiator and completer, these two assumptions are equivalent in the low-dose region; for a promoter, using the fraction of lifetime risk assumption is generally more conservative than that of the fraction of lifetime dose rate assumption. Tables are constructed to show that the use of either the fraction of lifetime dose rate assumption or the fraction lifetime risk assumption can both underestimate and overestimate the true risk for the three types of carcinogens.     

Empirical Bayes rules and Gaussian processes

In this paper we study empirical Bayes (e.B.) rules from a viewpoint which has not yet got any attention in the literature. Since an e.B. estimator can be seen as an estimate of an unknown function, namely the true Bayes estimator, it is natural to consider e.B. estimators as stochastic processes. In this paper we make a first attempt in the direction of this approach. For a certain class of e.B. estimators for the continuous one-parameter exponential family, we investigate the global behaviour on finite intervals. It is shown that the difference between the e.B. and the true Bayes estimator can be represented as a certain type of Gaussian process plus a remainder which is uniformly of smaller order. Several applications of this result are given.     

Judgment and Analysis in Oil Spill Risk Assessment

The risk of oil spills is a major environmental issue in the siting of proposed coastal refineries, oil terminals, deepwater ports, and in the leasing of offshore lands for oil exploration and development. As with any kind of risk, oil spill risk assessment is inherently judgmental and no analytic method can eliminate the need for judgment. This paper compares representative examples of oil spill risk assessments with regard to decisions about data, variables, functional relations, and uncertainty. The comparison emphasizes the judgmental basis of analytic methods.     

Issues in Qualitative and Quantitative Risk Analysis for Developmental Toxicology1

The qualitative and quantitative evaluation of risk in developmental toxicology has been discussed in several recent publications.(^1–3) A number of issues still are to be resolved in this area. The qualitative evaluation and interpretation of end points in developmental toxicology depends on an understanding of the biological events leading to the end points observed, the relationships among end points, and their relationship to dose and to maternal toxicity. The interpretation of these end points is also affected by the statistical power of the experiments used for detecting the various end points observed. The quantitative risk assessment attempts to estimate human risk for developmental toxicity as a function of dose. The current approach is to apply safety (uncertainty) factors to die no observed effect level (NOEL). An alternative presented and discussed here is to model the experimental data and apply a safety factor to an estimated risk level to achieve an “acceptable” level of risk. In cases where the dose-response curves upward, this approach provides a conservative estimate of risk. This procedure does not preclude the existence of a threshold dose. More research is needed to develop appropriate dose-response models that can provide better estimates for low-dose extrapolation of developmental effects.