Mediation in der Schule Ein Praxisbericht aus hessischen Projektschulen

Mediation in school. A case report about Hessian project schoolsOn the basis of four examples from his practical experience, a Hessian school-mediator illustrates both the immediate profit of mediation for the conflicting parties and the influence of the training ground of mediation for personal development, as well as the importance for professional qualification. Mediation is presented both as an educational and a political model which needs for its development a systemic concept. Various building blocks for a concept of constructive conflict resolution are presented. The considerations lead to a long-term objective of a democratic school, with a high degree of participation from all members of the school community.     

The level and uncertainty of inflation: results from OECD forecasts

There is considerable evidence that inflation variability and the level of inflation are positively related across countries. Evidence of a within-country relation is mixed. Evidence for a significant positive relation comes mostly from studies using some survey measure; contrary evidence comes mostly from studies using regression errors. Our measure of uncertainty is the squared forecast-error from Organization for Economic Cooperation and Development inflation forecasts. Most countries do not exhibit a positive and significant relation. The greatest number of positive coefficients is for relative uncertainty regressed on contemporaneous inflation.     

Evaluation of the importance of ornamental plants for pollinators in urban and suburban areas in Stuttgart,Germany

Urban Ecosystems - Urban landscapes are often characterized by a wide range of diverse flowering plants consisting of native and exotic plants. These flower-rich habitats have proven to be...     

Empirical Bayes estimators in hierarchical models with mixture priors

We consider subgroup analyses within the framework of hierarchical modeling and empirical Bayes (EB) methodology for general priors, thereby generalizing the normal–normal model. By doing this one obtains greater flexibility in modeling. We focus on mixture priors, that is, on the situation where group effects are exchangeable within clusters of subgroups only. We establish theoretical results on accuracy, precision, shrinkage and selection bias of EB estimators under the general priors. The impact of model misspecification is investigated and the applicability of the methodology is illustrated with datasets from the (medical) literature.     

Another view on the analysis of cardiovascular morbidity/mortality trials

In many morbidity/mortality studies, composite endpoints are considered. Although the primary interest is to demonstrate that an invention delays death, the expected death rate is often that low that studies focussing on survival exclusively are not feasible. Components of the composite endpoint are chosen such that their occurrence is predictive for time to death. Therefore, if the time to non-fatal events is censored by death, censoring is no longer independent. As a consequence, the analysis of the components of a composite endpoint cannot be reasonably performed using classical methods for the analysis of survival times like Kaplan-Meier estimates or log-rank tests. In this paper we visualize the impact of disregarding dependent censoring during the analysis and discuss practicable alternatives for the analysis of morbidity/mortality studies. In the context of simulations we provide evidence that copula-based methods have the potential to deliver practically unbiased estimates of hazards of components of a composite endpoint. At the same time, they require minimal assumptions, which is important since not all assumptions are generally verifiable because of censoring. Therefore, there are alternative ways to analyze morbidity/mortality studies more appropriately by accounting for the dependencies among the components of composite endpoints. Despite the limitations mentioned, these alternatives can at minimum serve as sensitivity analyses to check the robustness of the currently used methods.     

Subgroup analysis and interpretation for phase 3 confirmatory trials: White paper of the EFSPI/PSI working group on subgroup analysis

Subgroup by treatment interaction assessments are routinely performed when analysing clinical trials and are particularly important for phase 3 trials where the results may affect regulatory labelling. Interpretation of such interactions is particularly difficult, as on one hand the subgroup finding can be due to chance, but equally such analyses are known to have a low chance of detecting differential treatment effects across subgroup levels, so may overlook important differences in therapeutic efficacy. EMA have therefore issued draft guidance on the use of subgroup analyses in this setting. Although this guidance provided clear proposals on the importance of pre‐specification of likely subgroup effects and how to use this when interpreting trial results, it is less clear which analysis methods would be reasonable, and how to interpret apparent subgroup effects in terms of whether further evaluation or action is necessary. A PSI/EFSPI Working Group has therefore been investigating a focused set of analysis approaches to assess treatment effect heterogeneity across subgroups in confirmatory clinical trials that take account of the number of subgroups explored and also investigating the ability of each method to detect such subgroup heterogeneity. This evaluation has shown that the plotting of standardised effects, bias‐adjusted bootstrapping method and SIDES method all perform more favourably than traditional approaches such as investigating all subgroup‐by‐treatment interactions individually or applying a global test of interaction. Therefore, these approaches should be considered to aid interpretation and provide context for observed results from subgroup analyses conducted for phase 3 clinical trials.     

A note on the Hodges–Lehmann estimator

The Hodges‐Lehmann estimator was originally developed as a non‐parametric estimator of a shift parameter. As it is widely used in statistical applications, the question is investigated what it is estimating if the shift model does not hold. It is shown that for data whose distributions are symmetric about their median the Hodges–Lehmann estimator based on the Wilcoxon Rank Sum test estimates the difference between the medians of the distributions. This result does generally not hold if the symmetry assumption is violated. Copyright © 2009 John Wiley & Sons, Ltd.