Alternative Methods for Computing the Sensitivity of Complex Surveillance Systems

Stochastic scenario trees are a new and popular method by which surveillance systems can be analyzed to demonstrate freedom from pests and disease. For multiple component systems—such as a combination of a serological survey and systematically collected observations—it can be difficult to represent the complete system in a tree because many branches are required to represent complex conditional relationships. Here we show that many of the branches of some scenario trees have identical outcomes and are therefore redundant. We demonstrate how to prune branches and derive compact representations of scenario trees using matrix algebra and Bayesian belief networks. The Bayesian network representation is particularly useful for calculation and exposition. It therefore provides a firm basis for arguing disease freedom in international forums.     

Estimating utility functions using generalized maximum entropy

This paper estimates von Neumann and Morgenstern utility functions using the generalized maximum entropy (GME), applied to data obtained by utility elicitation methods. Given the statistical advantages of this approach, we provide a comparison of the performance of the GME estimator with ordinary least square (OLS) in a real data small sample setup. The results confirm the ones obtained for small samples through Monte Carlo simulations. The difference between the two estimators is small and it decreases as the width of the parameter support vector increases. Moreover, the GME estimator is more precise than the OLS one. Overall, the results suggest that GME is an interesting alternative to OLS in the estimation of utility functions when data are generated by utility elicitation methods.     

Quantitative Risk Assessment of Listeria monocytogenes in French Cold-Smoked Salmon: II. Risk Characterization

A model for the assessment of exposure to Listeria monocytogenes from cold-smoked salmon consumption in France was presented in the first of this pair of articles (Pouillot et al ., 2007, Risk Analysis, 27:683–700). In the present study, the exposure model output was combined with an internationally accepted hazard characterization model, adapted to the French situation, to assess the risk of invasive listeriosis from cold-smoked salmon consumption in France in a second-order Monte Carlo simulation framework. The annual number of cases of invasive listeriosis due to cold-smoked salmon consumption in France is estimated to be 307, with a very large credible interval ([10; 12,453]), reflecting data uncertainty. This uncertainty is mainly associated with the dose-response model. Despite the significant uncertainty associated with the predictions, this model provides a scientific base for risk managers and food business operators to manage the risk linked to cold-smoked salmon contaminated with L. monocytogenes. Under the modeling assumptions, risk would be efficiently reduced through a decrease in the prevalence of L. monocytogenes or better control of the last steps of the cold chain (shorter and/or colder storage during the consumer step), whereas reduction of the initial contamination levels of the contaminated products and improvement in the first steps of the cold chain do not seem to be promising strategies. An attempt to apply the recent risk-based concept of FSO (food safety objective) on this example underlines the ambiguity in practical implementation of the risk management metrics and the need for further elaboration on these concepts.     

A simulation study of the nearest neighbour analysis method of papadakis

The relative performances of randomised block, balanced lattice squares and Papadakis nearest neighbour analyses were compared on two simulated fields whose soil heterogeneity profiles were generated, one with a few evenly spaced contours and the other with many unevenly spaced contours. Four levels of random error were generated to simulate different proportions of random error and soil heterogeneity. Dummy treatments, corresponding to 7 x 7 and 11 x 11 balanced lattice squares were applied to the fields. The results from simulated experiments showed an interaction of error mean square (EMS) between size of experiment (7 x 7, 11 x 11) and levels of soil heterogeneity in the lattice analyses, but no such interaction in the Papadakis analyses. The Papadakis EMS decreased as random error decreased but at a rate depending on the map andthe ratio of soil heterogeneity to random error.     

Immigrants and Employer-provided Training

Much has been written about the labour market outcomes for immigrants in their host countries, particularly with regard to earnings, employment and occupational attainment. However, much less attention has been paid to the question of whether immigrants are as likely to receive employer-provided training relative to comparable natives. As such training should be crucial in determining the labour market success of immigrants in the long run it is a critically important question. Using data from a large-scale survey of employees in Ireland, we find that immigrants are less likely to receive training from employers, with immigrants from the New Member States of the EU experiencing a particular disadvantage. The immigrant training disadvantage arises in part from a failure on the part of immigrants to get employed by training-oriented firms. However, they also experience a training disadvantage relative to natives within firms where less training is provided.     

The Impact of Remittances on Nutritional Status of Children in Ecuador1

This work analyzes the impact of remittances on nutritional status of children aged <5 years old in Ecuador in 2006. Using a set of anthropometric indicators constructed according to the new World Health Organization standards, the last household survey available for this country, and an instrumental variables strategy controlling for endogeneity of remittances, this study finds a positive and significant effect of remittance income on short-term and middle-term child nutritional status; nevertheless, no significant impact on long-run anthropometric indicators.     

Use of several auxiliary variables in estimating the population mean in a two-occasion rotation pattern

ABSTRACT

This paper addresses the problem of estimation of the population mean on the current (second) occasion in two-occasion successive sampling. Utilizing the readily available information on several auxiliary variables on both occasions and the information on the study variable from the previous occasion, an estimation procedure of the population mean on the current occasion has been proposed. Theoretical properties of the proposed estimator have been investigated. Optimum replacement policy to the proposed estimator has been discussed. The proposed estimator has been compared empirically with the sample mean estimator, when there is no matching and the optimum estimator which is a linear combination of the means of the matched and unmatched portions of the sample at the current occasion. Appropriate recommendations have been made for practical applications.     

Leitung mit Supervisionskompetenz

The author describes a position of a supervisor in a clinical institution, which he would have rejected some years ago??to adopt a management role as supervisor and to act mainly in the role of a supervisor. But the recent experiences have shown, that this may be possible and successful. This is illustrated by a case study.     

Adaptive confidence bands in the nonparametric fixed design regression model

In this note, we consider the problem of the existence of adaptive confidence bands in the fixed design regression model, adapting ideas in Hoffmann and Nickl [(2011), ‘On Adaptive Inference and Confidence Bands’, Annals of Statistics, 39, 2383–2409] to the present case. In the course of the proof, we show that sup-norm adaptive estimators exist as well in the regression setting.     

TQM: Some issues for deliberation

In this note, the author puts forth some fundamental but generic issues arising from evolving theories and practices of TQM and suggests an agenda for furtherance of research.