Valuation of childhood risk reduction: the importance of age, risk preferences, and perspective.

This article explores two problems analysts face in determining how to estimate values for children's health and safety risk reductions. The first addresses the question: Do willingness‐to‐pay estimates for health risk changes differ across children and adults and, if so, how? To answer this question, the article first examines the potential effects of age and risk preferences on willingness to pay. A summary of the literature reporting empirical evidence of differences between willingness to pay for adult health and safety risk reductions and willingness to pay for health and safety risk reductions in children is also provided. The second dimension of the problem is a more fundamental issue: Whose perspective is relevant when valuing children's health effects—society's, children's, adults‐as‐children, or parents'? Each perspective is considered, followed ultimately by the conclusion that adopting a parental perspective through an intrahousehold allocation model seems closest to meeting the needs of the estimation problem at hand. A policy example in which the choice of perspective affects the outcome of a regulatory benefit‐cost analysis rounds out the article and emphasizes the importance of perspective.     

Stress at work and psychological and immunological parameters in a group of Norwegian female bank employees

This study concerned the immunological correlates of stress and work. Self reported stress, emotional state, ego-strength, and defensiveness were examined in relation to measures of cellular immunity (T-cell response to Con A and number of T4 and T8 cells) and humoral immunity (concentrations of immunoglobulins and complement components in plasma) in a group of 96 Norwegian female bank employees. The analyses showed that workload, the stress factor with the highest group mean, was associated with number of T-cells, while strain due to body posture during work was related to concentrations of IgM and C3. Further, depression was significantly correlated with IgM concentration and T-cell number, and anxiety with C3 concentration. T-cell activity was the immunological parameter most consistently associated with psychological well-being, showing positive correlations with defensiveness and ego-strength and negative correlations with anxiety and depression. In conclusion, T-cell number and concentrations of IgM and C3 were sensitive to both work-related stress experience and emotional distress. Coping abilities, indicated by the MMPI Ego-strength scale and emotional distress, were reflected in T-cell activity; insufficient coping was associated with low T-cell activity.     

Constructivist self-development theory: a theoretical framework for assessing and treating traumatized college students.

The authors present a new conceptual framework for assessing and treating traumatized college students. The framework, constructivist self-development theory (CSDT), blends object relations, self-psychology, and social cognition theories. It is founded upon a constructivist view of trauma in which the individual's unique history shapes his or her experience of traumatic events and defines the adaptation to trauma. Within this theory, the authors suggest approaches to setting the frame for trauma therapy, including stabilizing acute symptoms and setting appropriate expectations for treatment. CSDT provides a framework for the systematic assessment and practical treatment of three aspects of the self that are affected by trauma. These include self-capacities, or the ability to tolerate strong affect and regulate self-esteem; cognitive schemas, or beliefs and expectations about self and others in the areas of frame of reference (or identity and world view), safety, trust, esteem, intimacy, power, and independence; and intrusive trauma memories and related distressing affect. Finally, the authors provide guidelines for assessing the need for longer term treatment.     

Girls’ Jobs for the Boys? Men,Masculinity and Non‐Traditional Occupations

Occupational segregation by sex remains the most pervasive aspect of the labour market. In the past, most research on this topic has concentrated on explanations of women’s segregation into low paid and low status occupations, or investigations of women who have crossed gender boundaries into men’s jobs, and the potential impact on them and the occupations. In contrast, this article reports on a small‐scale, qualitative study of ten men who have crossed into what are generally defined as ‘women’s jobs’. In doing so, one of the impacts on them has been that they have experienced challenges to their masculine identity from various sources and in a variety of ways. The men’s reactions to these challenges, and their strategies for developing and accommodating their masculinity in light of these challenges, are illuminating. They either attempted to maintain a traditional masculinity by distancing themselves from female colleagues, and/or partially (re)constructed a different masculinity by identifying with their non‐traditional occupations. This they did as often as they deemed necessary as a response to different forms of challenge to their gender identities from both men and women. Finally, the article argues that these responses work to maintain the men as the dominant gender, even in these traditionally defined ‘women’s jobs’.     

Membranes, mitochondria and amoebae: shape models

Most real-world shapes and images are characterized by high variability- they are not rigid, like crystals, for example—but they are strongly structured. Therefore, a fundamental task in the understanding and analysis of such image ensembles is the construction of models that incorporate both variability and structure in a mathematically precise way. The global shape models introduced in Grenander's general pattern theory are intended to do this. In this paper, we describe the representation of two-dimensional mitochondria and membranes in electron microscope photographs, and three-dimensional amoebae in optical sectioning microscopy. There are three kinds of variability to all of these patterns, which these representations accommodate. The first is the variability in shape and viewing orientation. For this, the typical structure is represented via linear, circular and spherical templates, with the variability accomodated via the application of transformations applied to the templates. The transformations form groups: scale, rotation and translation. They are locally applied throughout the continuum and of high dimension. The second is the textural variability; the inside and outside of these basic shapes are subject to random variation, as well as sensor noise. For this, statistical sensor models and Markov random field texture models are used to connect the constituent structures of the shapes to the measured data. The third variability type is associated with the fact that each scene is made up of a variable number of shapes; this number is not assumed to be known a priori. Each scene has a variable number of parameters encoding the transformations of the templates appropriate for that scene. For this, a single posterior distribution is defined over the countable union of spaces representing models of varying numbers of shapes. Bayesian inference is performed via computation of the conditional expectation of the parametrically defined shapes under the posterior. These conditional mean estimates are generated using jump-diffusion processes. Results for membranes, mitochondria and amoebae are shown.     

A bayesian estimator for the dependence function of a bivariate extreme‐value distribution

Any continuous bivariate distribution can be expressed in terms of its margins and a unique copula. In the case of extreme‐value distributions, the copula is characterized by a dependence function while each margin depends on three parameters. The authors propose a Bayesian approach for the simultaneous estimation of the dependence function and the parameters defining the margins. They describe a nonparametric model for the dependence function and a reversible jump Markov chain Monte Carlo algorithm for the computation of the Bayesian estimator. They show through simulations that their estimator has a smaller mean integrated squared error than classical nonparametric estimators, especially in small samples. They illustrate their approach on a hydrological data set.     

在应对入世后我国农业面临的挑战中分析测试技术和科学仪器担负的重任

本文概叙了入世后中国农业面临的农产品品质 安全性及价格的三重冲击和应采取的应对措施 着重分析了农产品安全问题和食品安全保障体系的构建 论述了分析测试技术和科学仪器的七项重任     

A Non-parametric Frailty Model for Temporally Clustered Multivariate Failure Times

Abstract A model is introduced here for multivariate failure time data arising from heterogenous populations. In particular, we consider a situation in which the failure times of individual subjects are often temporally clustered, so that many failures occur during a relatively short age interval. The clustering is modelled by assuming that the subjects can be divided into ‘internally homogenous’ latent classes, each such class being then described by a time‐dependent frailty profile function. As an example, we reanalysed the dental caries data presented earlier in Härkänen et al. [Scand. J. Statist. 27 (2000) 577], as it turned out that our earlier model could not adequately describe the observed clustering.     

Which Wald statistic? Choosing a parameterization of the Wald statistic to maximize power in k-sample generalized estimating equations

The Wald statistic is known to vary under reparameterization. This raises the question: which parameterization should be chosen, in order to optimize power of the Wald statistic? We specifically consider k-sample tests of generalized linear models (GLMs) and generalized estimating equations (GEEs) in which the alternative hypothesis contains only two parameters. An example is presented in which such an alternative hypothesis is of interest. Amongst a general class of parameterizations, we find the parameterization that maximizes power via analysis of the non-centrality parameter, and show how the effect on power of reparameterization depends on sampling design and the differences in variance across samples. There is no single parameterization with optimal power across all alternatives. The Wald statistic commonly used under the canonical parameterization is optimal in some instances but it performs very poorly in others. We demonstrate results by example and by simulation, and describe their implications for likelihood ratio statistics and score statistics. We conclude that due to poor power properties, the routine use of score statistics and Wald statistics under the canonical parameterization for GEEs is a questionable practice.