Negative Acculturation and Nothing More? Cumulative Disadvantage and Mortality during the Immigrant Adaptation Process among Latinos in the United States

Foreign‐ and U.S.‐born Hispanic health deteriorates with increasing exposure and acculturation to mainstream U.S. society. Because these associations are robust to (static) socioeconomic controls, negative acculturation has become their primary explanation. This overemphasis, however, has neglected important alternative structural explanations. Examining Hispanic mortality using the 1998–2006 U.S. National Health Interview Survey‐Linked Mortality File according to nativity, immigrant adaptation measures, and health behaviors, this study presents indirect but compelling evidence that suggests negative acculturation is not the only or main explanation for this deterioration.     

Capability indices for Birnbaum–Saunders processes applied to electronic and food industries

Process capability indices (PCIs) are tools widely used by the industries to determine the quality of their products and the performance of their manufacturing processes. Classic versions of these indices were constructed for processes whose quality characteristics have a normal distribution. In practice, many of these characteristics do not follow this distribution. In such a case, the classic PCIs must be modified to take into account the non-normality. Ignoring the effect of this non-normality can lead to misinterpretation of the process capability and ill-advised business decisions. An asymmetric non-normal model that is receiving considerable attention due to its good properties is the Birnbaum–Saunders (BS) distribution. We propose, develop, implement and apply a methodology based on PCIs for BS processes considering estimation, parametric inference, bootstrap and optimization tools. This methodology is implemented in the statistical software {\tt R}. A simulation study is conducted to evaluate its performance. Real-world case studies with applications for three data sets are carried out to illustrate its potentiality. One of these data sets was already published and is associated with the electronic industry, whereas the other two are unpublished and associated with the food industry.     

A method for combining inference across related nonparametric Bayesian models

Summary.  We consider the problem of combining inference in related nonparametric Bayes models. Analogous to parametric hierarchical models, the hierarchical extension formalizes borrowing strength across the related submodels. In the nonparametric context, modelling is complicated by the fact that the random quantities over which we define the hierarchy are infinite dimensional. We discuss a formal definition of such a hierarchical model. The approach includes a regression at the level of the nonparametric model. For the special case of Dirichlet process mixtures, we develop a Markov chain Monte Carlo scheme to allow efficient implementation of full posterior inference in the given model.     

A semi‐Markovian approach to using event history data in multiregional demography

As a first step towards infusing event‐history analysis into multiregional demography, this paper introduces a semi‐Markovian framework and outlines its salient features as differentiated from a pure Markovian framework. Specifically, what differentiates the former from the latter is an explicit consideration of duration‐dependence in migrating from one region to another. This duration‐dependence is one of the complexities involved in using event‐history data in multiregional demography. The use of event‐history data lends itself easily to defining basic probabilities involved in a semi‐Markovian framework directly on sample paths of individuals. The underlying concepts of a semi‐Markov process in the special case of time‐homogeneity or age‐independence of transition probabilities are given in a coherent and concise form. Illustrations of empirical applications to the event‐history data on migration as provided by the Korean National Migration Survey conducted in 1983, and of distinct features of the semi‐Markovian analysis through a parametrization of the basic probabilities are also given in this paper.     

Integration of the information systems in the production process: a case study

This paper evaluates the execution of an ERP – enterprise resource planning in a production process. The changes that were made to processes to make them compatible with ERP modules and adaptations that were required by the ERP implementation are presented. The presented study is different from the normal patterns of a vertical implementation, since its application is not direct. In order to use the standard modules of the ERP system, the internal processes were embellished and the data collection steps were integrated into the production process (production orders, inventory, production, daily consumption, daily output). The case study shows that the ERP implementation caused an improvement of the processes in the areas adjacent to production (purchasing, logistics, distribution, supply and sales). In conclusion, this paper presents the main advantages and disadvantages of the ERP system implementation, as well as some considerations and recommendations for the future ERP implementations.