Analysis of hybrid censored competing risks data

In this paper, we consider the analysis of hybrid censored competing risks data, based on Cox's latent failure time model assumptions. It is assumed that lifetime distributions of latent causes of failure follow Weibull distribution with the same shape parameter, but different scale parameters. Maximum likelihood estimators (MLEs) of the unknown parameters can be obtained by solving a one-dimensional optimization problem, and we propose a fixed-point type algorithm to solve this optimization problem. Approximate MLEs have been proposed based on Taylor series expansion, and they have explicit expressions. Bayesian inference of the unknown parameters are obtained based on the assumption that the shape parameter has a log-concave prior density function, and for the given shape parameter, the scale parameters have Beta–Gamma priors. We propose to use Markov Chain Monte Carlo samples to compute Bayes estimates and also to construct highest posterior density credible intervals. Monte Carlo simulations are performed to investigate the performances of the different estimators, and two data sets have been analysed for illustrative purposes.     

Positive False Discovery Rate Estimate in Step-Wise Variable Selection

Selecting predictors to optimize the outcome prediction is an important statistical method. However, it usually ignores the false positives in the selected predictors. In this article, we advocate a conventional stepwise forward variable selection method based on the predicted residual sum of squares, and develop a positive false discovery rate (pFDR) estimate for the selected predictor subset, and a local pFDR estimate to prioritize the selected predictors. This pFDR estimate takes account of the existence of non null predictors, and is proved to be asymptotically conservative. In addition, we propose two views of a variable selection process: an overall and an individual test. An interesting feature of the overall test is that its power of selecting non null predictors increases with the proportion of non null predictors among all candidate predictors. Data analysis is illustrated with an example, in which genetic and clinical predictors were selected to predict the cholesterol level change after four months of tamoxifen treatment, and pFDR was estimated. Our method's performance is evaluated through statistical simulations.     

Robust Correlation Structure for Multivariate Failure Time Data

When incomplete repeated failure times are collected from a large number of independent individuals, interest is focused primarily on the consistent and efficient estimation of the effects of the associated covariates on the failure times. Since repeated failure times are likely to be correlated, it is important to exploit the correlation structure of the failure data in order to obtain such consistent and efficient estimates. However, it may be difficult to specify an appropriate correlation structure for a real life data set. We propose a robust correlation structure that can be used irrespective of the true correlation structure. This structure is used in constructing an estimating equation for the hazard ratio parameter, under the assumption that the number of repeated failure times for an individual is random. The consistency and efficiency of the estimates is examined through a simulation study, where we consider failure times that marginally follow an exponential distribution and a Poisson distribution is assumed for the random number of repeated failure times. We conclude by using the proposed method to analyze a bladder cancer dataset.     

An Optimization‐Based Framework for the Identification of Vulnerabilities in Electric Power Grids Exposed to Natural Hazards

This article proposes a novel mathematical optimization framework for the identification of the vulnerabilities of electric power infrastructure systems (which is a paramount example of critical infrastructure) due to natural hazards. In this framework, the potential impacts of a specific natural hazard on an infrastructure are first evaluated in terms of failure and recovery probabilities of system components. Then, these are fed into a bi‐level attacker–defender interdiction model to determine the critical components whose failures lead to the largest system functionality loss. The proposed framework bridges the gap between the difficulties of accurately predicting the hazard information in classical probability‐based analyses and the over conservatism of the pure attacker–defender interdiction models. Mathematically, the proposed model configures a bi‐level max‐min mixed integer linear programming (MILP) that is challenging to solve. For its solution, the problem is casted into an equivalent one‐level MILP that can be solved by efficient global solvers. The approach is applied to a case study concerning the vulnerability identification of the georeferenced RTS24 test system under simulated wind storms. The numerical results demonstrate the effectiveness of the proposed framework for identifying critical locations under multiple hazard events and, thus, for providing a useful tool to help decisionmakers in making more‐informed prehazard preparation decisions.     

中国基本医疗保险的实际参保率及其分布特征:基于多源数据的分析

全民覆盖是基本医疗保险降低国民医疗费用负担的前提条件。中国基本医疗保险是否实现了全民覆盖仍存在争议。本文利用多源调查数据,分析了我国基本医疗保险实际参保率及其分布特征。不同来源的数据基本证实,2015-2016年,中国仍有超过10%的国民没有参加任何一项基本医疗保险制度。其中,城镇居民、非农户口和没有户口的居民、东北地区、年轻人、儿童、未就业人群、低收入人群、在校学生以及流动人口基本医疗保险实际参保率更低。城乡居民实行自愿参保,因管理部门分割、信息系统不统一导致的重复参保以及因财政补贴制度导致的户籍地参保等制度设计,是导致基本医疗保险未能实现全民覆盖的根源。要实现基本医疗保险全民覆盖,解决国民医疗后顾之忧,未来我国基本医疗保险应实行强制参保、以家庭为单元参保、常住地参保,建立全国统一的基本医疗保险信息系统,并鼓励发展补充性医疗保障制度。     

Toward an Application Guide for Safety Integrity Level Allocation in Railway Systems

The work in the article presents the development of an application guide based on feedback and comments stemming from various railway actors on their practices of SIL allocation to railway safety‐related functions. The initial generic methodology for SIL allocation has been updated to be applied to railway rolling stock safety‐related functions in order to solve the SIL concept application issues. Various actors dealing with railway SIL allocation problems are the intended target of the methodology; its principles will be summarized in this article with a focus on modifications and precisions made in order to establish a practical guide for railway safety authorities. The methodology is based on the flowchart formalism used in CSM (common safety method) European regulation. It starts with the use of quantitative safety requirements, particularly tolerable hazard rates (THR). THR apportioning rules are applied. On the one hand, the rules are related to classical logical combinations of safety‐related functions preventing hazard occurrence. On the other hand, to take into account technical conditions (last safety weak link, functional dependencies, technological complexity, etc.), specific rules implicitly used in existing practices are defined for readjusting some THR values. SIL allocation process based on apportioned and validated THR values is finally illustrated through the example of “emergency brake” subsystems. Some specific SIL allocation rules are also defined and illustrated.     

企业利用FTA出口的影响因素分析

当前,以FTA为代表的区域贸易协定正逐渐成为各国开展经济战略合作与竞争的重要手段,但是现实中我国企业对FTA的利用率并不高。为了探寻其中的原因,首先从FTA使用成本和收益的角度建立了一个分析影响企业FTA利用率的理论模型,探讨了企业FTA策略选择背后的作用机制。其次,基于2017年中国—东盟FTA的问卷调查数据,利用有序probit模型进行了实证研究,发现企业获取FTA信息的难易程度、申请原产地证书的时间等FTA使用成本是影响中国企业FTA利用率的重要因素;利用FTA出口则有助于企业增加出口量,使其出口产品更具价格优势,并有助于企业加入全球/区域生产网络和产品供应链。最后,异质性检验结果表明,相对于生产型企业,获取FTA信息困难程度的降低、企业申请原产地证书时间的缩短等更有利于提高外贸型企业的FTA利用率;大规模企业对FTA的利用率受FTA使用所得收益的影响较大,而小规模企业对FTA的利用率则对FTA使用成本更为敏感。为了提高企业对FTA的利用率,政府应当扩大对FTA相关政策的宣传,提高企业的认知水平,同时简化各种审批手续,努力缩短原产地证书申请所需时间。