Testing Supremacy or Inferiority of Multinomial Cell Probabilities with Application to Biting Preferences of Loggerhead Marine Turtles

We propose exact tests for uniform superiority or uniform inferiority of a multinomial cell probability. We extend the approach to testing supremacy or inferiority in multivariate settings. We also show how to perform superiority or inferiority tests in presence of covariates, and discuss the different interpretations of the proposed tests. The tests are illustrated on an original data set on biting behavior of loggerhead marine turtles.     

Criminal Victimization and Crime Risk Perception: A Multilevel Longitudinal Study

In a national sample of the Italian population, surveyed four times between October 2002 and January 2007 (N = 2,008), we performed a multilevel longitudinal study aimed at predicting the increase in crime risk perception as a function of three families of independent variables, respectively lying at the within individual level (direct victimization and indirect victimization), at the between-individuals level (being a woman, being an older person, being a poorly educated person and size of area of residence) and at the ecological level (county’s crime rate, unemployment rate and immigration rate). Direct and indirect victimization, being a woman, being an older person, living in a large town and in a context characterized by high crime and unemployment rates positively influenced the change in crime risk perception, while the other individual and ecological predictors we used in our predictive model did not. Strengths, limitations, implications and future developments of this research are discussed.     

Profiles of distress in sheltered battered women: implications for intervention

Heterogeneity in patterns of distress and psychological functioning was investigated using a person-oriented approach to data analysis in two diverse samples of battered women in shelters. In order to provide some empirically derived guidance to clinicians, scores on measures of depressive symptoms as well as state and trait anxiety were cluster analyzed. A four-cluster solution provided the best fit for both samples of women, and despite the demographic differences in the women, generally similar clusters were found in both samples. One cluster contained women with minimal distress; another, those who were mildly anxious; in a third cluster, the women were moderately to highly depressed and anxious; and in a fourth cluster, the women were reporting severe levels of distress. Implications for treatment include the importance of providing individually tailored interventions for the women, based on differential combinations of depression and anxiety, especially for women whose distress levels are in the high and severe ranges of distress.     

Efficient or Fair? Operationalizing Ethical Principles in Flood Risk Management: A Case Study on the Dutch-German Rhine

Flood risk management decisions in many countries are based on decision-support frameworks which rely on cost-benefit analyses. Such frameworks are seldom informative about the geographical distribution of risk, raising questions on the fairness of the proposed policies. In the present work, we propose a new decision criterion that accounts for the distribution of risk reduction and apply it to support flood risk management decisions on a transboundary stretch of the Rhine River. Three types of interventions are considered: embankment heightening, making Room for the River, and changing the discharge distribution of the river branches. The analysis involves solving a flood risk management problem according to four alternative formulations, based on different ethical principles. Formulations based on cost optimization lead to very poor performances in some areas for the sake of reducing the overall aggregated costs. Formulations that also include equity criteria have different results depending on how these are defined. When risk reduction is distributed equally, very poor economic performance is achieved. When risk is distributed equally, results are in line with formulations based on cost optimization, while a fairer risk distribution is achieved. Risk reduction measures also differ, with the cost optimization approach strongly favoring the leverage of changing the discharge distribution and the alternative formulations spending more on embankment heightening and Room for the River, to rebalance inequalities in risk levels. The proposed method advances risk-based decision-making by allowing to consider risk distribution aspects and their impacts on the choice of risk reduction measures.     

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.     

Impact measurement and dimension reduction of auxiliary variables in calibration estimator using the Shapley decomposition

Statistical Methods & Applications - In multipurpose surveys several interest variables and a very large number of auxiliary variables are collected. Auxiliary variables are usually considered...