Nonparametric adaptive likelihood weights

The weighted likelihood can be used to make inference about one population when data from similar populations are available. The author shows heuristically that the weighted likelihood can be seen as a special case of the entropy maximization principle. This leads him to propose the minimum averaged mean squared error (MAMSE) weights. He describes an algorithm for calculating these weights and shows its convergence using the Kuhn‐Tucker conditions. He explores the performance and properties of the weighted likelihood based on MAMSE weights through simulations.     

Risk patterns in drug safety study using relative times by accelerated failure time models when proportional hazards assumption is questionable: an illustrative case study of cancer risk of patients on glucose‐lowering therapies

Observational drug safety studies may be susceptible to confounding or protopathic bias. This bias may cause a spurious relationship between drug exposure and adverse side effect when none exists and may lead to unwarranted safety alerts. The spurious relationship may manifest itself through substantially different risk levels between exposure groups at the start of follow‐up when exposure is deemed too short to have any plausible biological effect of the drug. The restrictive proportional hazards assumption with its arbitrary choice of baseline hazard function renders the commonly used Cox proportional hazards model of limited use for revealing such potential bias. We demonstrate a fully parametric approach using accelerated failure time models with an illustrative safety study of glucose‐lowering therapies and show that its results are comparable against other methods that allow time‐varying exposure effects. Our approach includes a wide variety of models that are based on the flexible generalized gamma distribution and allows direct comparisons of estimated hazard functions following different exposure‐specific distributions of survival times. This approach lends itself to two alternative metrics, namely relative times and difference in times to event, allowing physicians more ways to communicate patient's prognosis without invoking the concept of risks, which some may find hard to grasp. In our illustrative case study, substantial differences in cancer risks at drug initiation followed by a gradual reduction towards null were found. This evidence is compatible with the presence of protopathic bias, in which undiagnosed symptoms of cancer lead to switches in diabetes medication. Copyright © 2015 John Wiley & Sons, Ltd.     

An Approximate Bayesian Algorithm for Combining Forecasts*

In this paper we propose a consensus forecasting method based on a convex combination of individual forecast densities. The exact Bayesian updating of the convex combination weights is very complex and practically prohibitive. We propose a simple sequential updating alternative method based on function approximation. Several examples illustrate the method.     

Beyond the Disciplinary Role of Governance: How Boards Add Value to Spanish Foundations

Due to the significant role of non‐profit organizations in the development of modern societies, these organizations must adjust their boardrooms. Since traditional theories of corporate governance appear to be limited in explaining the changing non‐profit world, we propose an extended model of governance that integrates the traditional arguments of agency theory with a cognitive dimension. Based on a sample of Spanish foundations, we present evidence on the effect of the board composition on foundations' organizational efficiency. We show that board size and independence do not have a definitive effect on the entity's efficiency. Instead, the knowledge diversity inside the boardroom and the active character of trustees have a positive influence on resource allocation. The cognitive dimension of the extended model of governance is critical to explaining how boards impact on organizational performance.     

Critical Theorist,Postmodernist and Social Constructionist Paradigms in Organizational Analysis: A Paradigmatic Review of Organizational Learning Literature

In an effort to clarify alternative approaches to organizational analysis, this paper is concerned to stimulate the debate on how an inquiry into organizational phenomena, in general, and organizational learning, in particular, can be accomplished. Encouraging attention to different aspects of various paradigmatic approaches, the paper focuses on critical theory, postmodernism and social constructionism and how these paradigms have contributed and can contribute to the research in the subject domain of organizational learning. To this end, a paradigmatic review of the literature on organizational learning is offered in this paper. Organizational learning, as the study of learning processes of, and within, organizations, has attracted significant attention in academe since the early 1980s. There is a plethora of studies on organizational learning, which offer rich material for a paradigmatic review. This study highlights the need for further development of the field from alternative paradigmatic perspectives, with a view to generating more insights into the multifaceted, complex and changing nature of learning in contemporary organizations.     

Integrated Approaches for the Public Health Prioritization of Foodborne and Zoonotic Pathogens

To address the persistent problems of foodborne and zoonotic disease, public health officials worldwide face difficult choices about how to best allocate limited resources and target interventions to reduce morbidity and mortality. Data‐driven approaches to informing these decisions have been developed in a number of countries. Integrated comparative frameworks generally share three methodological components: estimating incidence of acute illnesses, chronic sequelae, and mortality; attributing pathogen‐specific illnesses to foods; and calculating integrated measures of disease burden such as cost of illness, willingness to pay, and health‐adjusted life years (HALYs). To discuss the similarities and differences in these approaches, to seek consensus on principles, and to improve international collaboration, the E.U. MED‐VET‐NET and the U.S.‐based Food Safety Research Consortium organized an international conference convened in Berlin, Germany, on July 19–21, 2006. This article draws in part on the deliberations of the conference and discusses general principles, data needs, methodological issues and challenges, and future research needs pertinent to objective data‐driven analyses and their potential use for priority setting of foodborne and zoonotic pathogens in public health policy.     

Global Sensitivity Analysis Applied to a Contamination Assessment Model of Listeria monocytogenes in Cold Smoked Salmon at Consumption

In this study, a variance‐based global sensitivity analysis method was first applied to a contamination assessment model of Listeria monocytogenes in cold smoked vacuum packed salmon at consumption. The impact of the choice of the modeling approach (populational or cellular) of the primary and secondary models as well as the effect of their associated input factors on the final contamination level was investigated. Results provided a subset of important factors, including the food water activity, its storage temperature, and duration in the domestic refrigerator. A refined sensitivity analysis was then performed to rank the important factors, tested over narrower ranges of variation corresponding to their current distributions, using three techniques: ANOVA, Spearman correlation coefficient, and partial least squares regression. Finally, the refined sensitivity analysis was used to rank the important factors.     

A Quantitative Assessment of the Risk for Highly Pathogenic Avian Influenza Introduction into Spain via Legal Trade of Live Poultry

Highly pathogenic avian influenza (HPAI) is considered one of the most important diseases of poultry. During the last 9 years, HPAI epidemics have been reported in Asia, the Americas, Africa, and in 18 countries of the European Union (EU). For that reason, it is possible that the risk for HPAI virus (HPAIV) introduction into Spain may have recently increased. Because of the EU free‐trade policy and because legal trade of live poultry was considered an important route for HPAI spread in certain regions of the world, there are fears that Spain may become HPAIV‐infected as a consequence of the legal introduction of live poultry. However, no quantitative assessment of the risk for HPAIV introduction into Spain or into any other EU member state via the trade of poultry has been published in the peer‐reviewed literature. This article presents the results of the first quantitative assessment of the risk for HPAIV introduction into a free country via legal trade of live poultry, along with estimates of the geographical variation of the risk and of the relative contribution of exporting countries and susceptible poultry species to the risk. The annual mean risk for HPAI introduction into Spain was estimated to be as low as 1.36 × 10⁻³, suggesting that under prevailing conditions, introduction of HPAIV into Spain through the trade of live poultry is unlikely to occur. Moreover, these results support the hypothesis that legal trade of live poultry does not impose a significant risk for the spread of HPAI into EU member states.     

Large Risks,Limited Liability,and Dynamic Moral Hazard

We study a continuous‐time principal–agent model in which a risk‐neutral agent with limited liability must exert unobservable effort to reduce the likelihood of large but relatively infrequent losses. Firm size can be decreased at no cost or increased subject to adjustment costs. In the optimal contract, investment takes place only if a long enough period of time elapses with no losses occurring. Then, if good performance continues, the agent is paid. As soon as a loss occurs, payments to the agent are suspended, and so is investment if further losses occur. Accumulated bad performance leads to downsizing. We derive explicit formulae for the dynamics of firm size and its asymptotic growth rate, and we provide conditions under which firm size eventually goes to zero or grows without bounds.     

The Rationality of Under‐employing the Best‐performing Soccer Players

Abstract. This paper analyses the influence of sport performance (productivity) and other variables measuring the economic contribution of soccer players, upon the coach's decision of selecting a particular player. Using as dependent variable the proportion of time that individuals play in the Spanish professional soccer league, the paper concludes that players' economic market value does significantly affect the coach's choice, revealing the existence of other aims different from maximizing sport performance. We also examine the type of discrimination associated with lower chances of playing, which leads to smaller earnings and poorer career opportunities. The empirical evidence does not support discrimination due to nationality.