Estimating and comparing adverse event probabilities in the presence of varying follow-up times and competing events

Safety analyses of adverse events (AEs) are important in assessing benefit–risk of therapies but are often rather simplistic compared to efficacy analyses. AE probabilities are typically estimated by incidence proportions, sometimes incidence densities or Kaplan–Meier estimation are proposed. These analyses either do not account for censoring, rely on a too restrictive parametric model, or ignore competing events. With the non-parametric Aalen-Johansen estimator as the “gold standard”, that is, reference estimator, potential sources of bias are investigated in an example from oncology and in simulations, for both one-sample and two-sample scenarios. The Aalen-Johansen estimator serves as a reference, because it is the proper non-parametric generalization of the Kaplan–Meier estimator to multiple outcomes. Because of potential large variances at the end of follow-up, comparisons also consider further quantiles of the observed times. To date, consequences for safety comparisons have hardly been investigated, the impact of using different estimators for group comparisons being unclear. For example, the ratio of two both underestimating or overestimating estimators may not be comparable to the ratio of the reference, and our investigation also considers the ratio of AE probabilities. We find that ignoring competing events is more of a problem than falsely assuming constant hazards by the use of the incidence density and that the choice of the AE probability estimator is crucial for group comparisons.     

论市场经济背景下儒家伦理精神的现代转换

儒家伦理精神是对封建政治制度和自然经济制度合理性的道德注脚。重义轻利、重和息争、重德轻法、重群轻己、等级森严等儒家伦理精神,是自然经济和家国同构的产物,具有显著的历史局限性。儒家伦理精神只有进行创造性转换,赋予时代内涵,才能适应社会主义市场经济发展的需要:将重义轻利转换为义利统一、重和息争转换为竞合精神、重德轻法转换为德法并重、重群轻己转换为群己兼顾、等级观念转换为自由平等。      

Bounds in Competing Risks Models and the War on Cancer

In 1971, President Nixon declared war on cancer. Thirty years later, many declared this war a failure: the age‐adjusted mortality rate from cancer in 2000 was essentially the same as in the early 1970s. Meanwhile the age‐adjusted mortality rate from cardiovascular disease fell dramatically. Since the causes that underlie cancer and cardiovascular disease are likely dependent, the decline in mortality rates from cardiovascular disease may partially explain the lack of progress in cancer mortality. Because competing risks models (used to model mortality from multiple causes) are fundamentally unidentified, it is difficult to estimate cancer trends. We derive bounds for aspects of the underlying distributions without assuming that the underlying risks are independent. We then estimate changes in cancer and cardiovascular mortality since 1970. The bounds for the change in duration until death for either cause are fairly tight and suggest much larger improvements in cancer than previously estimated.     

团队学习的过程、条件与氛围

组织中的知识分为隐性知识和显性知识两种,团队学习过程就是两种知识相互转化的过程。然而,团队学习过程并不能凭空产生,需要一定条件和氛围。文章将团队学习的条件分为物理空间、虚拟空间和心智空间三种。对团队学习的氛围着重讨论了团队自治、绩效评估与激励系统、团队持续性三个方面。     

论平台“封禁”的反垄断规制

随着数字化进程的不断推进,互联网人口红利见底,国内数字市场进入存量竞争阶段,互联网平台间竞争加剧,以“封禁”为典型的反竞争行为呈现频繁化、规模化、常态化趋势。在扩张多元市场、构建产业生态体系之际,社交平台运用封禁手段把控流量入口,在严重影响生态外竞争对手的产品和服务之余,也形成了市场准入和拓展壁垒,抑制了市场竞争活力和创新动力,侵害了消费者和社会公共利益,逐渐成为阻碍数字经济健康发展的症结所在。故此,应立足于《反垄断法》,结合数字经济竞争特点,洞悉平台流量垄断本质,构建多元而动态的反垄断规制体系。一是要发展监管科技,保障平台行为动态合规,适当施以平台开放义务,弱化事后处罚机制。二是要充分考量竞争损害的构成要素,重构反垄断分析范式。三是要把握市场公平与效率的动态平衡,必要时以结构性救济为兜底保障。     

Analysis of fracture toughness data

In studies of the fracture toughness of irradiated weld metal, specimens are subjected to an increasing load. The test on any one specimen might be terminated by choice or because the specimen ruptures. Prior to termination, ductile tearing might or might not have occurred. The situation is thus basically one of competing risks, with different types of termination, but there are additional features. The major purpose of statistical analysis is to estimate probabilities concerning the values of toughness and crack length. The analysis has been based on a model developed for the joint survivor function of these quantities.     

Competing risks quantile regression at work: in-depth exploration of the role of public child support for the duration of maternity leave

Despite its emergence as a frequently used method for the empirical analysis of multivariate data, quantile regression is yet to become a mainstream tool for the analysis of duration data. We present a pioneering empirical study on the grounds of a competing risks quantile regression model. We use large-scale maternity duration data with multiple competing risks derived from German linked social security records to analyse how public policies are related to the length of economic inactivity of young mothers after giving birth. Our results show that the model delivers detailed insights into the distribution of transitions out of maternity leave. It is found that cumulative incidences implied by the quantile regression model differ from those implied by a proportional hazards model. To foster the use of the model, we make an R-package (cmprskQR) available.     

Statistical inference of Marshall-Olkin bivariate Weibull distribution with three shocks based on progressive interval censored data

There are several failure modes may cause system failed in reliability and survival analysis. It is usually assumed that the causes of failure modes are independent each other, though this assumption does not always hold. Dependent competing risks modes from Marshall-Olkin bivariate Weibull distribution under Type-I progressive interval censoring scheme are considered in this paper. We derive the maximum likelihood function, the maximum likelihood estimates, the 95% Bootstrap confidence intervals and the 95% coverage percentages of the parameters when shape parameter is known, and EM algorithm is applied when shape parameter is unknown. The Monte-Carlo simulation is given to illustrate the theoretical analysis and the effects of parameters estimates under different sample sizes. Finally, a data set has been analyzed for illustrative purposes.     

Approximate Identifiability, Moments and Censored Data

It is well known that the joint distribution of a pair of random variables ( X,Y ) is not identifiable on the basis of the joint distribution of the function (min ( X,Y ), 1[ X < Y ]). This paper introduces the concept of approximate identifiability and studies its relevance to the function (min ( X,Y ), Y ). It shows that the distribution of ( X,Y ) is approximately identifiable on the basis of the distribution of (min ( X,Y ), Y ). The identification is explicitly executed by a method of moments. The method is applied to the analysis of censored distributions arising in the theory of clinical trials and is compared to the standard method of Kaplan and Meier.