Preference orderings represented by coherent upper and lower conditional previsions

Theory and Decision - Preference orderings assigned by coherent lower and upper conditional previsions are defined and they are considered to define maximal random variables and Bayes random...     

Perinatal loss and parental grief: the challenge of ambiguity and disenfranchised grief

Following perinatal loss, a type of ambiguous loss, bereaved couples struggle with and experience distress due to various forms of ambiguity. Moreover, the juxtaposition of their grief with society's minimization often disenfranchises them from traditional grieving processes. The purpose of this study was to explore sources of ambiguity and disenfranchised grief related to perinatal loss. Audio-taped interviews with 13 bereaved couples at 2, 6, and 13 months following the death of their fetus or infant were analyzed. Several categories of ambiguity and disenfranchised grief emerged, pertaining to: (a) the viability of the pregnancy; (b) the physical process of pregnancy loss; (c) making arrangements for the remains; and (d) sharing the news. This study uncovers the many sources of ambiguity and disenfranchised grief that bereaved couples face in interactions with family, friends, society, and healthcare professionals. These insights may inform healthcare professionals in their attempts to ease distress related to perinatal loss.     

Grief and loss of religion: the experiences of four rural lesbians

The purpose of this four-person study was to discover the grief and loss experiences of rural lesbians using a phenomenological approach. A prominent theme that emerged from the interview data was grief and loss related to religion and a lesbian identity. Participants identified the need to modify their beliefs, the experience of rejection by church members or the church itself, and seeking acceptance.     

Is more better? The relationship between outcomes achieved by problem gamblers and the number of counselling sessions attended

Abstract

This paper addresses the question of how much intervention is necessary for the effective treatment of problem gambling by exploring the relationship between the number of counselling sessions attended and the degree of problem resolution achieved for 613 individuals who attended problem gambling counselling services in Victoria. While those who achieved partial or full resolution of presenting problems attended more sessions than those who finished counselling with their problems still unresolved, problems were typically reported as being resolved in fewer than five sessions. It is concluded that for some problem gamblers a relatively brief intervention may be sufficient.     

Bayesian univariate space-time hierarchical model for mapping pollutant concentrations in the municipal area of Taranto

An analysis of air quality data is provided for the municipal area of Taranto (Italy) characterized by high environmental risks as decreed by the Italian government in the 1990s. In the context of an agreement between Dipartimento di Scienze Statistiche—Università degli Studi di Bari and the local regional environmental protection agency air quality, data were provided concerning six monitoring stations and covering years from 2005 to 2007. In this paper we analyze the daily concentrations of three pollutants highly relevant in such an industrial area, namely SO₂, NO₂ and PM₁₀, with the aim of reconstructing daily pollutants concentration surfaces for the town area. Taking into account the large amount of sparse missing data and the non normality affecting pollutants’ concentrations, we propose a full Bayesian separable space-time hierarchical model for each pollutant concentration series. The proposed model allows to embed missing data imputation and prediction of pollutant concentration. We critically discuss the results, highlighting advantages and disadvantages of the proposed methodology.     

Confidence Intervals for Diffusion Index Forecasts and Inference for Factor‐Augmented Regressions

We consider the situation when there is a large number of series, N, each with T observations, and each series has some predictive ability for some variable of interest. A methodology of growing interest is first to estimate common factors from the panel of data by the method of principal components and then to augment an otherwise standard regression with the estimated factors. In this paper, we show that the least squares estimates obtained from these factor‐augmented regressions are consistent and asymptotically normal if . The conditional mean predicted by the estimated factors is consistent and asymptotically normal. Except when T/N goes to zero, inference should take into account the effect of “estimated regressors” on the estimated conditional mean. We present analytical formulas for prediction intervals that are valid regardless of the magnitude of N/T and that can also be used when the factors are nonstationary.