Bayesian analysis of elapsed times in continuous‐time Markov chains

The authors consider Bayesian analysis for continuous‐time Markov chain models based on a conditional reference prior. For such models, inference of the elapsed time between chain observations depends heavily on the rate of decay of the prior as the elapsed time increases. Moreover, improper priors on the elapsed time may lead to improper posterior distributions. In addition, an infinitesimal rate matrix also characterizes this class of models. Experts often have good prior knowledge about the parameters of this matrix. The authors show that the use of a proper prior for the rate matrix parameters together with the conditional reference prior for the elapsed time yields a proper posterior distribution. The authors also demonstrate that, when compared to analyses based on priors previously proposed in the literature, a Bayesian analysis on the elapsed time based on the conditional reference prior possesses better frequentist properties. The type of prior thus represents a better default prior choice for estimation software.     

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.     

A global count of the extreme poor in 2012: data issues,methodology and initial results

The 2014 release of a new set of purchasing power parity (PPP) conversion factors (PPPs) for 2011 has prompted a revision of the World Bank’s international poverty line. In revising the line, we have sought to minimize changes to the real purchasing power of the earlier $1.25 line (in 2005 PPPs), so as to preserve the integrity of the goalposts for international targets such as the Sustainable Development Goals (SDGs) and the World Bank’s twin goals – which were set with respect to that line. In particular, the new line was obtained by inflating the same fifteen national poverty lines – originally used by Ravallion et al. (World Bank Econ. Rev. 23(2): 163–184 2009) to construct the $1.25 line – to 2011 prices in local currency units, and then converting them to US dollars using 2011 PPP conversion factors. With a small approximation, this procedure yields a new international poverty line of $1.90 per person per day. In combination with other changes described in the paper, this revision leads to relatively small changes in global poverty incidence for 2011: from 14.5 % using the old method to 14.1 % using the new method. In 2012, the new reference year for the global count, we find 12.7 % of the world’s population, or 897 million people, are living in extreme poverty. There are changes in the regional composition of poverty, but they are also relatively small. This paper documents methodological decisions taken in the process of updating both the poverty line and the consumption and income distributions at the country level, including issues of inter-temporal and spatial price adjustments. It also describes various caveats and limitations of the approach taken.     

Proposal for training of workers and researchers as from the participatory return of research results in workers' health

This study streams from a perspective of Workers' Health as a field of intervention where worker's experience on the process of illness is essential to understand and generate changes in the work process, and to contribute to develop knowledge in this area. We intended to collaborate in the training of researchers and nursing workers as a means of contributing to amplify their knowledge related to work and health conditions. As a motto to promote dialogue between researchers and workers, we organized workshops to discuss the results of an epidemiological study on the work-health relationships in nursing. Ten workshops were conducted at two federal public hospitals, in the city of Rio de Janeiro, Brazil. The main aspects discussed during the workshops revealed (i) work nuances for which the questionnaire was not sufficiently sensitive, (ii) some associations between different aspects of the survey, dealt with in the questionnaires, and (iii) recognition that some aspects shown in the epidemiological results were experienced at work. One can appreciate that the proposal presented here contributed to the training of researchers and workers, amplifying their knowledge and contributing to the development of the activity.     

Ergonomics and the inclusion of people with disabilities in a Brazilian workplace

The customization of a secretary workstation at a drama school was the objective of this case study. The investigation involved a 25-year-old illiterate woman with intellectual disabilities and low vision that had been been attending, for over 12 years, a state school for people with disabilities. The customization process, operationalized after a diagnosis was made, focused on environmental rearrangements, with the purpose of meeting the physical and social demands of the workstation. The results of this research are configured in an ergonomic analysis of work associated with an inventory of social skills, applied to people living directly with the participant. Preliminary evaluations indicated the degree of adjustment of labor demands to the personal characteristics of the participant in the customized job.     

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.     

A Comparison of Hierarchical Methods for Clustering Functional Data

Functional data analysis (FDA)—the analysis of data that can be considered a set of observed continuous functions—is an increasingly common class of statistical analysis. One of the most widely used FDA methods is the cluster analysis of functional data; however, little work has been done to compare the performance of clustering methods on functional data. In this article, a simulation study compares the performance of four major hierarchical methods for clustering functional data. The simulated data varied in three ways: the nature of the signal functions (periodic, non periodic, or mixed), the amount of noise added to the signal functions, and the pattern of the true cluster sizes. The Rand index was used to compare the performance of each clustering method. As a secondary goal, clustering methods were also compared when the number of clusters has been misspecified. To illustrate the results, a real set of functional data was clustered where the true clustering structure is believed to be known. Comparing the clustering methods for the real data set confirmed the findings of the simulation. This study yields concrete suggestions to future researchers to determine the best method for clustering their functional data.     

University Students’ Attitudes Toward Same-Sex Parenting and Gay and Lesbian Rights in Portugal

The purpose of this study was to explore university students’ attitudes toward same-sex parenting and toward gay and lesbian rights. A total of 292 participants, aged between 18 and 27 (M = 21) responded to a questionnaire measuring attitudes toward parenting by gay men and lesbians, gay and lesbian rights, and beliefs about the etiology of homosexuality. Results revealed that the majority of students were against gay and lesbian parenting, gay and lesbian equal rights, and believed that homosexuality has a social/environmental basis. It was found that sexual prejudice is highly prevalent in Portuguese university students, and implications of these findings are discussed.