Estimation and diagnostic analysis in skew-generalized-normal regression models

The skew-generalized-normal distribution [Arellano-Valle, RB, Gómez, HW, Quintana, FA. A new class of skew-normal distributions. Comm Statist Theory Methods 2004;33(7):1465–1480] is a class of asymmetric normal distributions, which contains the normal and skew-normal distributions as special cases. The main virtues of this distribution is that it is easy to simulate from and it also supplies a genuine expectation–maximization (EM) algorithm for maximum likelihood estimation. In this paper, we extend the EM algorithm for linear regression models assuming skew-generalized-normal random errors and we develop a diagnostics analyses via local influence and generalized leverage, following Zhu and Lee's approach. This is because Cook's well-known approach would be more complicated to use to obtain measures of local influence. Finally, results obtained for a real data set are reported, illustrating the usefulness of the proposed method.     

Model averaging inconcentration–QT analyses

This article describes how a frequentist model averaging approach can be used for concentration–QT analyses in the context of thorough QTc studies. Based on simulations, we have concluded that starting from three candidate model families (linear, exponential, and Emax) the model averaging approach leads to treatment effect estimates that are quite robust with respect to the control of the type I error in nearly all simulated scenarios; in particular, with the model averaging approach, the type I error appears less sensitive to model misspecification than the widely used linear model. We noticed also few differences in terms of performance between the model averaging approach and the more classical model selection approach, but we believe that, despite both can be recommended in practice, the model averaging approach can be more appealing because of some deficiencies of model selection approach pointed out in the literature. We think that a model averaging or model selection approach should be systematically considered for conducting concentration–QT analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

Ergonomics in projects of oil platforms in a change context

The context of oil platform design is changing in order to increase competitiveness and be prepared for difficult operations, mainly in fields more distant from the coast, like pre-salt. The currently preceding context is marked by projects guidelines designed to reduce projects and operation costs, including an important reducing in the number of people on board. The main objective of this research is to verify and discuss if the experience of use in platforms designed in a previous context, in which the people on board is practically twice, can contribute and/or can be transferred to new projects. From the ergonomic intervention in the design of two oil platform, with the work of team on board investigated on previous projects as reference, it was possible analyze if the previous use is still applicable to new projects. As a result, about 90% of the recommendations based on use are applicable to the current context. The restrictions on the transfer or operational experience are mainly related to the time of entry of ergonomics in the design process, the subsequent transformations costs and the advance of the execution phase started with the detailed design.     

Estimation and diagnostic for skew-normal partially linear models

Partially linear models (PLMs) are an important tool in modelling economic and biometric data and are considered as a flexible generalization of the linear model by including a nonparametric component of some covariate into the linear predictor. Usually, the error component is assumed to follow a normal distribution. However, the theory and application (through simulation or experimentation) often generate a great amount of data sets that are skewed. The objective of this paper is to extend the PLMs allowing the errors to follow a skew-normal distribution [A. Azzalini, A class of distributions which includes the normal ones, Scand. J. Statist. 12 (1985), pp. 171–178], increasing the flexibility of the model. In particular, we develop the expectation-maximization (EM) algorithm for linear regression models and diagnostic analysis via local influence as well as generalized leverage, following [H. Zhu and S. Lee, Local influence for incomplete-data models, J. R. Stat. Soc. Ser. B 63 (2001), pp. 111–126]. A simulation study is also conducted to evaluate the efficiency of the EM algorithm. Finally, a suitable transformation is applied in a data set on ragweed pollen concentration in order to fit PLMs under asymmetric distributions. An illustrative comparison is performed between normal and skew-normal errors.     

Is the Way Young People Drive a Reflection of the Way Their Parents Drive? An Econometric Study of the Relation Between Parental Risk and Their Children's Risk

This article aims to investigate parental influence on high-risk behavior by young people. Although research on the topic of perception of risk demonstrates that it is socially constructed, the role of the family in this construction has rarely been studied. Using a French national survey of more than 1,200 young drivers between the ages of 18 and 25, and their parents, we attempt to understand the transmission of risk within families. Our econometric study shows that parents influence both the practices and representations of their children. When parental norms and values are transmitted, they are by no means accepted in a wholly passive way. Indeed, the parental model is in competition with other models that originate from both inside the family (brothers and sisters) and outside it (instructors). Furthermore, parental influence decreases over time as young people become more experienced drivers and construct their own identity with regard to risk.     

The Structure of Mental Health: Higher-Order Confirmatory Factor Analyses of Psychological Distress and Well-Being Measures

Social Indicators Research - This paper addresses the question of whether psychological distress and subjective well-being are the opposite poles of the same axis of mental health or independent...     

Personality and Subjective Well-Being: What Hides Behind Global Analyses?

The relation between personality and subjective well-being (SWB) remains involved in a considerable ambiguity and the numerous studies conducted have neglected an approach at a more detailed level of analysis. This study explores the idea that neuroticism, extraversion and conscientiousness facets predict differentially each SWB component. A battery of self-report questionnaires was used to assess personality and SWB in 398 teachers of primary and high schools. Findings of a cross-sectional study showed that neuroticism, extraversion and conscientiousness facets contributed to significantly explain the variance in positive affect, negative affect and life satisfaction. Moreover, these facets predicted differentially each of the three SWB components. At same time, this study corroborates two important premises: the specificity of facets as discrete traits and the independence of the three SWB components.     

Promouvoir le pouvoir collectif des travailleurs dans les réseaux de production mondialisés: retour sur une occasion manquée

L'auteur s'interroge sur la capacité des ONG de renforcer le pouvoir collectif du travail au sein des réseaux de production mondialisés en utilisant leur pouvoir de pression sur les multinationales pour lancer des programmes d'élections de comités de travailleurs dans les usines. Sur la base d'une enquête empirique menée entre 2012 et 2019 dans le sud de la Chine, il montre que ces programmes ont permis de sensibiliser les travailleurs à l'action collective et de renforcer leur agentivité, mais que l'inégalité structurelle du système de production, l'absence de protection institutionnelle en faveur des représentants élus et le durcissement du régime ont empêché qu'ils perdurent.