A theorem for Bayesian group decisions

This paper presents a natural extension of Bayesian decision theory from the domain of individual decisions to the domain of group decisions. We assume that each group member accepts the assumptions of subjective expected utility theory with respect to the alternatives from which they must choose, but we do not assume, a priori, that the group as a whole accepts those assumptions. Instead, we impose a multiattribute utility independence condition on the preferences of the group with respect to the expected utilities of its actions as appraised by its members. The result is that the expected utility of an alternative for the group is a weighted average of the expected utilities of that alternative for its members. The weights must be determined collectively by the group. Pareto optimality is not assumed, though the result is consistent with Pareto optimality.     

Prespective from a weather modification experiment

This article provides some views on the statistical design and analysis of weather modification experiments. Perspectives were developed from experience with analyses of the Santa Barbara Phase I experiment summarized in Section 2, Randomization analvses are reported and compared with previously published parametric analyses. The parametric significance levels of tests for a cloud seeding effect agree well with the significance levels of the new corresponding randomization tests, These results, along with similar results of others, suggest that parametric analyses may be used as approximations to randomization analyses in exploratory analyses or reanalyses of weather modification experimental data.     

Model-based adaptive spatial sampling for occurrence map construction

In many environmental management problems, the construction of occurrence maps of species of interest is a prerequisite to their effective management. However, the construction of occurrence maps is a challenging problem because observations are often costly to obtain (thus incomplete) and noisy (thus imperfect). It is therefore critical to develop tools for designing efficient spatial sampling strategies and for addressing data uncertainty. Adaptive sampling strategies are known to be more efficient than non-adaptive strategies. Here, we develop a model-based adaptive spatial sampling method for the construction of occurrence maps. We apply the method to estimate the occurrence of one of the world’s worst invasive species, the red imported fire ant, in and around the city of Brisbane, Australia. Our contribution is threefold: (i) a model of uncertainty about invasion maps using the classical image analysis probabilistic framework of Hidden Markov Random Fields (HMRF), (ii) an original exact method for optimal spatial sampling with HMRF and approximate solution algorithms for this problem, both in the static and adaptive sampling cases, (iii) an empirical evaluation of these methods on simulated problems inspired by the fire ants case study. Our analysis demonstrates that the adaptive strategy can lead to substantial improvement in occurrence mapping.     

Illness-death model: statistical perspective and differential equations

The aim of this work is to relate the theory of stochastic processes with the differential equations associated with multistate (compartment) models. We show that the Kolmogorov Forward Differential Equations can be used to derive a relation between the prevalence and the transition rates in the illness-death model. Then, we prove mathematical well-definedness and epidemiological meaningfulness of the prevalence of the disease. As an application, we derive the incidence of diabetes from a series of cross-sections.     

FEAR OF CRIME IN URBAN RESIDENTIAL NEIGHBORHOODS:

Current work on fear of crime centers largely around three dominant theoretical models: indirect victimization, community concern, and incivilities. Previous work (Taylor and Hale 1986) confirms the importance of the central construct in each model and shows that no one model has more explanatory power than another. But work to date has not examined ecological impacts of some key constructs, even though the models clearly imply processes operative at the neighborhood level. This study extends earlier work, combining central predictors from each model and distinguishing between- and within-neighborhood sources of impact, with data from surveys of 1622 residents of 66 Baltimore neighborhoods and from on-site assessments. Findings indicate ways in which these theories, particularly indirect victimization and incivilities, need further theoretical articulation of central constructs. The results also confirm the generalizability of Merry's diversity thesis—developed from field work in a multi-ethnic subsidized housing context—to urban neighborhoods in a major metropolitan area.     

Discrimination indexes and models for studying sensory functioning in aging

A popular paradigm in experimental psychophysics has subjects estimate sensation magnitude by assigning numbers to stimuli in some way. While it is typical to analyze the central tendency (e.g. means and slopes) of the subjects' psychophysical. functions, there is often a greater need to analyze the internal consistency of these functions. A subject who gives increasing mean responses across increasing stimulus intensities and also gives highly consistent responses within stimulus intensities is showing superior sensory discrimination. We propose new discrimination indexes, based on measures of association and lack-of-fit, that summarize monotonic regressions of the subject's data, as well as non-metric and metric-sensitive measures related to Kendall's coefficient of concordance. We use these indexes in quadratic spline regression models for cross-sectional age trends in sensory discrimination, with covariates included to adjust for task demands and gender differences.Because such data are potentially affected by increasing variability with age, we describe a method to assess this and adjust for it using reweighted least squares.     

Do union organizing activities affect decertification?

This paper tests the hypothesis that unions face a trade-off between retaining organized units and organizing new bargaining units. Using cost-benefit analysis, a model is developed which examines the impact of representation elections on the level of decertification activity for the period 1948 to 1979. The results indicate that as unions increase their efforts to organize more employees, they trade-off a loss of membership through decertification. The shift of resources from servicing existing units to organizing new units causes a sufficient change in the benefit/cost ratio for employees to result in loss of union certification.