Nested exposure case-control sampling: a sampling scheme to analyze rare time-dependent exposures

For large cohort studies with rare outcomes, the nested case-control design only requires data collection of small subsets of the individuals at risk. These are typically randomly sampled at the observed event times and a weighted, stratified analysis takes over the role of the full cohort analysis. Motivated by observational studies on the impact of hospital-acquired infection on hospital stay outcome, we are interested in situations, where not necessarily the outcome is rare, but time-dependent exposure such as the occurrence of an adverse event or disease progression is. Using the counting process formulation of general nested case-control designs, we propose three sampling schemes where not all commonly observed outcomes need to be included in the analysis. Rather, inclusion probabilities may be time-dependent and may even depend on the past sampling and exposure history. A bootstrap analysis of a full cohort data set from hospital epidemiology allows us to investigate the practical utility of the proposed sampling schemes in comparison to a full cohort analysis and a too simple application of the nested case-control design, if the outcome is not rare.

     

制造企业服务业务扩展及其认知因素研究

制造企业的竞争越来越激烈,几乎所有的企业都要面对快速反应多变市场和应对价格压力的要求,面对越来越小的产品利润空间和越来越复杂的客户需求,本文从对工业服务管理文献分析和制造企业的调查研究入手,揭示了制造企业从纯粹的产品生产者向客户支持方案提供者发展的转移趋势.通过对瑞士和德国30多家机器和设备制造企业进行的调查研究,说明了服务业务对制造企业在开发财务、营销和战略机会上的重要作用,并对转移过程中服务业务的扩展过程进行了总结.结合具体企业实践,本文对制约制造企业扩展服务业务中在管理动机上的认知因素进行了分析和研究.结合中国加入WTO后,中国制造企业将全面融入国际竞争的背景,本文期望对中国制造企业的发展和竞争地位的提高提供理论和实践上的指导.     

Gentrifikation in zwei Wohngebieten von KölnGentrification in two residential areas of Cologne

We examine the process of Gentrification in two residential areas of Cologne, Germany: Deutz and Mülheim. The theory underlying the study is a phase (or stage) model of Gentrification in which indicators and their values are attributed to each phase. The hypotheses derived from the model pertain to changes in the social structure, rents and the spatial distribution of social groups such as “pioneers”, “gentrifiers” and “others”. We further assume both areas to be in different phases of Gentrification.     

Bargaining over waiting time in ultimatum game experiments

While preference-based explanations play an increasing role in economics and sociology, the accurate measurement of social preferences deserves more attention. Most laboratory experiments measure social preferences by studying the division of “a cake that nobody had to bake” (Güth and Kliemt, 2003). This article reports results of the first ultimatum game experiment with bargaining over waiting time. The experiment was created to avoid effects of windfall gains. In contrast to donated money, time is not endowed by the experimenter and implies a natural loss to subjects. This allows for a better measurement of the inherent conflict in the ultimatum game. We implemented three anonymity conditions; one baseline condition, one condition with anonymity among subjects and one double-blind condition in which the experimenter did not know the division of waiting time. While we expected to observe less other-regarding behavior in ultimatum game bargaining over time, our experimental results rather confirm previous ultimatum game experiments, in which people bargained over money. The modal offer was half of the waiting time and only one offer was rejected. Interestingly, anonymity did not change the results significantly. In conclusion, our experiment confirms other-regarding behavior in the ultimatum game.     

Sample size planning for phase II trials based on success probabilities for phase III

In recent years, high failure rates in phase III trials were observed. One of the main reasons is overoptimistic assumptions for the planning of phase III resulting from limited phase II information and/or unawareness of realistic success probabilities. We present an approach for planning a phase II trial in a time‐to‐event setting that considers the whole phase II/III clinical development programme. We derive stopping boundaries after phase II that minimise the number of events under side conditions for the conditional probabilities of correct go/no‐go decision after phase II as well as the conditional success probabilities for phase III. In addition, we give general recommendations for the choice of phase II sample size. Our simulations show that unconditional probabilities of go/no‐go decision as well as the unconditional success probabilities for phase III are influenced by the number of events observed in phase II. However, choosing more than 150 events in phase II seems not necessary as the impact on these probabilities then becomes quite small. We recommend considering aspects like the number of compounds in phase II and the resources available when determining the sample size. The lower the number of compounds and the lower the resources are for phase III, the higher the investment for phase II should be. Copyright © 2015 John Wiley & Sons, Ltd.     

The development of amyloid beta protein deposits in the aged brain

The deposition of amyloid beta protein (Abeta) in the human brain and the generation of neurofibrillary tangles are the histopathological hallmarks of Alzheimer's disease. Accumulation of Abeta takes place in senile plaques and in cerebrovascular deposits as a result of an imbalance between Abeta production and clearance. This Review describes the different types of Abeta deposits, which can be distinguished by their morphology and by the hierarchical involvement of distinct areas of the brain in Abeta deposition. The role of intracellular Abeta in Abeta deposition and the mechanism of Abeta toxicity are also discussed.     

Impaired Probability Estimation and Decision-Making in Pathological Gambling Poker Players

Poker has gained tremendous popularity in recent years, increasing the risk for some individuals to develop pathological gambling. Here, we investigated cognitive biases in a computerized two-player poker task against a fictive opponent, among 12 pathological gambling poker players (PGP), 10 experienced poker players (ExP), and 11 inexperienced poker players (InP). Players were compared on probability estimation and decision-making with the hypothesis that ExP would have significantly lower cognitive biases than PGP and InP, and that the groups could be differentiated based on their cognitive bias styles. The results showed that ExP had a significantly lower average error margin in probability estimation than PGP and InP, and that PGP played hands with lower winning probability than ExP. Binomial logistic regression showed perfect differentiation (100%) between ExP and PGP, and 90.5% classification accuracy between ExP and InP. Multinomial logistic regression showed an overall classification accuracy of 23 out of 33 (69.7%) between the three groups. The classification accuracy of ExP was higher than that of PGP and InP due to the similarities in probability estimation and decision-making between PGP and InP. These impairments in probability estimation and decision-making of PGP may have implications for assessment and treatment of cognitive biases in pathological gambling poker players.     

Progression-free survival in oncological clinical studies: Assessment time bias and methods for its correction

Progression-free survival (PFS) is a frequently used endpoint in oncological clinical studies. In case of PFS, potential events are progression and death. Progressions are usually observed delayed as they can be diagnosed not before the next study visit. For this reason potential bias of treatment effect estimates for progression-free survival is a concern. In randomized trials and for relative treatment effects measures like hazard ratios, bias-correcting methods are not necessarily required or have been proposed before. However, less is known on cross-trial comparisons of absolute outcome measures like median survival times. This paper proposes a new method for correcting the assessment time bias of progression-free survival estimates to allow a fair cross-trial comparison of median PFS. Using median PFS for example, the presented method approximates the unknown posterior distribution by a Bayesian approach based on simulations. It is shown that the proposed method leads to a substantial reduction of bias as compared to estimates derived from maximum likelihood or Kaplan–Meier estimates. Bias could be reduced by more than 90% over a broad range of considered situations differing in assessment times and underlying distributions. By coverage probabilities of at least 94% based on the credibility interval of the posterior distribution the resulting parameters hold common confidence levels. In summary, the proposed approach is shown to be useful for a cross-trial comparison of median PFS.