Subjective Welfare, Well-Being, and Self-Reported Food Hypersensitivity in Four European Countries: Implications for European Policy

This study estimates the effects of food hypersensitivity on individuals?? perceived welfare and well-being compared to non-food hypersensitive individuals. Study respondents were recruited in the Netherlands, Poland, Spain and UK. The difference in welfare between food hypersensitive respondents and those asymptomatic to foods was estimated using a subjective welfare approach, including income evaluation. Well-being was measured using the Cantril Ladder-of-Life Scale, and health status using the Self-Perceived Health Scale. The difference in well-being, welfare and health status between participant groups was explained further using a number of background variables. No significant within-country differences in welfare between food hypersensitive respondents and respondents asymptomatic to foods were found. In terms of well-being, adult food hypersensitive respondents and their spouses reported significantly less happiness than respondents and their spouses asymptomatic to foods in the Netherlands and Poland. In Spain, the spouses of the food hypersensitive respondents were significantly less happy than respondents aymptomatic to foods. The well-being of children did not significantly differ between groups. The degree of severity of food hypersensitivity was negatively related to overall health status. In Poland, food hypersensitive respondents reported worse health status compared to asymptomatic respondents. In Spain, the converse was true. Food hypersensitive respondents were generally less happy with their life as a whole than respondents asymptomatic to foods, presumably because they experienced more negative effects, which were not related to perceived health status.     

An empirical comparison of Canonical Correspondence Analysis and STATICO in the identification of spatio-temporal ecological relationships

The wide-ranging and rapidly evolving nature of ecological studies mean that it is not possible to cover all existing and emerging techniques for analyzing multivariate data. However, two important methods enticed many followers: the Canonical Correspondence Analysis (CCA) and the STATICO analysis. Despite the particular characteristics of each, they have similarities and differences, which when analyzed properly, can, together, provide important complementary results to those that are usually exploited by researchers. If on one hand, the use of CCA is completely generalized and implemented, solving many problems formulated by ecologists, on the other hand, this method has some weaknesses mainly caused by the imposition of the number of variables that is required to be applied (much higher in comparison with samples). Also, the STATICO method has no such restrictions, but requires that the number of variables (species or environment) is the same in each time or space. Yet, the STATICO method presents information that can be more detailed since it allows visualizing the variability within groups (either in time or space). In this study, the data needed for implementing these methods are sketched, as well as the comparison is made showing the advantages and disadvantages of each method. The treated ecological data are a sequence of pairs of ecological tables, where species abundances and environmental variables are measured at different, specified locations, over the course of time.     

Estimating infant mortality in Colombia: some overdispersion modelling approaches

It is common to fit generalized linear models with binomial and Poisson responses, where the data show a variability that is greater than the theoretical variability assumed by the model. This phenomenon, known as overdispersion, may spoil inferences about the model by considering significant parameters associated with variables that have no significant effect on the dependent variable. This paper explains some methods to detect overdispersion and presents and evaluates three well-known methodologies that have shown their usefulness in correcting this problem, using random mean models, quasi-likelihood methods and a double exponential family. In addition, it proposes some new Bayesian model extensions that have proved their usefulness in correcting the overdispersion problem. Finally, using the information provided by the National Demographic and Health Survey 2005, the departmental factors that have an influence on the mortality of children under 5 years and female postnatal period screening are determined. Based on the results, extensions that generalize some of the aforementioned models are also proposed, and their use is motivated by the data set under study. The results conclude that the proposed overdispersion models provide a better statistical fit of the data.     

Rivalry and strategic groups: what makes a company a rival?

Strategic group literature has generated a significant amount of research over recent decades. However, the rivalry implications of strategic group have remained unclear. This paper analyses rivalry and strategic groups in the house building industry in a small town from a cognitive approach. We consider rivalry as a subjective and directional phenomenon. Estimating rivalry as the direct identification of competitors we try to explain whether similarity affects rivalry and what factors make a company a “rival”. Results show that perceived rivalry is strongly related to size, past performance, subjective similarity and strategic group structure.

A reactive tabu search algorithm for the vehicle routing problem with simultaneous pickups and deliveries

The vehicle routing problem with pickups and deliveries (VRPPD) extends the vehicle routing problem (VRP) by allowing customers to both send and receive goods. The main difficulty of the problem is that the load of vehicles is fluctuating rather than decreasing as in the VRP. We design a reactive tabu search metaheuristic that can check feasibility of proposed moves quickly and reacts to repetitions to guide the search. Several new best solutions are found for benchmark problems.     

Therapeutic residential care in Spain. Population treated and therapeutic coverage

Therapeutic residential care (TRC) is the name given to specialized children's homes for treating cases with severe emotional and behavioural problems that have been placed in residential care. A recent international review has revealed great diversity in the referral criteria of cases and in the models of intervention carried out. The goal of this study is to describe the population treated in these types of facilities in Spain and the therapeutic coverage given. The sample is made up of 215 young people in children's homes, of whom 93 are in TRC. The cases referred to TRC have been in residential care for less time but have gone through a greater number of placements. These young people also exhibit more problems of drug use, and there is a larger percentage of clinical‐range cases in the Child Behaviour Checklist scales of attention problems and aggressive behaviour. Nevertheless, the results of logistic regression indicate that the only variables that significantly increase the probability of being referred to TRC are drug use and changes of care placements. With regard to therapeutic care, there is a higher percentage in the TRC group receiving psychiatric care, and the sessions are also more frequent.     

On a tobit–Birnbaum–Saunders model with an application to medical data

The tobit model allows a censored response variable to be described by covariates. Its applications cover different areas such as economics, engineering, environment and medicine. A strong assumption of the standard tobit model is that its errors follow a normal distribution. However, not all applications are well modeled by this distribution. Some efforts have relaxed the normality assumption by considering more flexible distributions. Nevertheless, the presence of asymmetry could not be well described by these flexible distributions. A real-world data application of measles vaccine in Haiti is explored, which confirms this asymmetry. We propose a tobit model with errors following a Birnbaum–Saunders (BS) distribution, which is asymmetrical and has shown to be a good alternative for describing medical data. Inference based on the maximum likelihood method and a type of residual are derived for the tobit–BS model. We perform global and local influence diagnostics to assess the sensitivity of the maximum likelihood estimators to atypical cases. A Monte Carlo simulation study is carried out to empirically evaluate the performance of these estimators. We conduct a data analysis for the mentioned application of measles vaccine based on the proposed model with the help of the R software. The results show the good performance of the tobit–BS model.     

The conditional maximum of Poisson random variables

The conditional maxima of independent Poisson random variables are studied. A triangular array of row-wise independent Poisson random variables is considered. If condition is given for the row-wise sums, then the limiting distribution of the row-wise maxima is concentrated onto two points. The result is in accordance with the classical result of Anderson. The case of general power series distributions is also covered. The model studied in Theorems 2.1 and 2.2 is an analogue of the generalized allocation scheme. It can be considered as a non homogeneous generalized scheme of allocations of at most n balls into N boxes. Then the maximal value of the contents of the boxes is studied.     

The Revenge of History – The Institutional Roots of Post‐Communist Family Policy in the Czech Republic,Hungary and Poland

The authors combine historical and sociological institutional analysis to show that despite the political and socio‐economic transformation in 1990s, the institutional development during and before the communist era provides the best explanation for current childcare policies in Central Europe. While most authors have concentrated on policy changes that have taken place in the region since 1989, this article concentrates on the historical roots of these policies and shows that today's policies are highly influenced by a certain dynamics that had already emerged under communist rule. It shows that a historical institutional approach, which analyses the ‘gendered logic of appropriateness’ and policy legacies at various critical junctures, can explain why family policies in Central Europe had already begun to differ during the communist era, why these main differences continue and why even the changes that have taken place follow logically from historical‐institutional developments.