R–estimation of normed bivariate density functions

Normed bivariate density funtions were introduced by HOEFFDING (1940/41). In the present paper estimators for normed bivariate ranks and on a FOURIER series expansion in LEGENDRE polynomials. The estimation of normed bivarate density functions under positive dependence is also described     

Changes in the structure of health complaints as related to shiftwork exposure

Abstract

Factor analyses of health complaints in groups with different length of shiftwork exposure show that the structure of these complaints changes with increasing shift experience, indicating the emergence of a shift-specific pattern of health complaints. After about 15 years of shiftwork, complaints related to disturbances of circadian-controlled functions can be found in the first factor whereas other complaints have their dominant loadings on a separate factor, representing general, non-shift-specific impairments. The results indicate that in this way shift-specific components of health impairment can be separated from other non-shift related components.     

A Comparison of Survival Function Estimators in the Koziol–Green Model

In this paper, three competing survival function estimators are compared under the assumptions of the so-called Koziol– Green model, which is a simple model of informative random censoring. It is shown that the model specific estimators of Ebrahimi and Abdushukurov, Cheng, and Lin are asymptotically equivalent. Further, exact expressions for the (noncentral) moments of these estimators are given, and their biases are analytically compared with the bias of the familiar Kaplan–Meier estimator. Finally, MSE comparisons of the three estimators are given for some selected rates of censoring.     

Micro‐level dynamics of social assistance receipt: Evidence from four European countries

This study investigated the monthly dynamics of social assistance benefit receipt – in particular the incidence of long‐term benefit receipt – in four European countries: Luxembourg, The Netherlands, Norway and Sweden. The analysis is based on four separate administrative panel data sets, each covering the 96‐month period from January 2001 to December 2008. Benefit dynamics were found to vary considerably across countries. In the two Nordic countries, long‐term benefit receipt was found to be a rare exception. Most recipients, however, had multiple spells and the majority of benefit leavers returned to benefits within a few months of leaving. In Luxembourg and The Netherlands, long‐term benefit receipt was frequent, but benefit leavers were much less likely to return to benefit receipt after exit. The total duration of benefit receipt per individual across spells was two to three times as high in The Netherlands and Luxembourg as in Norway and Sweden.     

Social workers' assessments of needs and interventions for adolescents with substance misuse problems,criminal behaviour and mental health difficulties: a vignette study

The aim of the current vignette study was to examine how social workers assess adolescents with substance misuse problems, criminal behaviour and mental health difficulties, and how they make decisions about treatment interventions to reduce these problems. Earlier research has shown lack of knowledge concerning factors and processes that govern assessments and decisions in social work practice. In this anonymously administered survey, social workers in Stockholm, Sweden, were invited to assess fictitious youth issues. We found that social workers recognise the problems and needs of young people, but that they find it harder to link needs to evidence-based interventions. Also, there is a tendency to overrate alleged non-serious problems in the vignettes. We conclude that there is a need for increased knowledge about evidence-based methods and more structured procedures to broaden the basis for decisions.     

A Quality Risk Management Model Approach for Cell Therapy Manufacturing

International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell‐based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator‐introduced variations, and affected by heterogeneity of the processed organs/tissues and lot‐dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell‐based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo‐quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed.     

Improving traceability in continuous processes using flow simulations

Traceability is normally difficult to achieve in continuous processes, since there are no natural batch structures. In this article, we demonstrate flow-based simulation using process data to improve traceability in a continuous pelletising process. Using the simulation model, the engineers could test the impacts of process disturbances, identify cause and effect relations and aid control in case of process disturbances. In a field trial where the chemistry of an additive was varied during production of a special product, the simulation forecasts predicted the level of the chemical content after the plant within the errors that the engineers found acceptable.