Each year, according to Chinese and European statistics, there are many serious injuries and even fatalities of travelers into subway transit stations. Consequently, it becomes more and more important for transit authorities to evaluate these facilities (platform, gates, stairs, escalators, etc.) under critical traffic conditions, such as rush hours or emergency situations. The purpose of this paper is to review existing research results, develop the main Framework of station capacity assessment and finally point out the key issues of subway station capacity assessment.
Methods for dealing with tied event times in the Cox proportional hazards model are well developed. Also, the partial likelihood provides a natural way to handle covariates that change over time. However, ties between event times and the times that discrete time-varying covariates change have not been systematically studied in the literature. In this article, we discuss the default behavior of current software and propose some simple methods for dealing with such ties. A simulation study shows that the default behavior of current software can lead to biased estimates of the coefficient of a binary time-varying covariate and that two proposed methods (Random Jitter and Equally Weighted) reduce estimation bias. The proposed methods can be easily implemented with existing software. The methods are illustrated on the well-known Stanford heart transplant data and data from a study on intimate partner violence and smoking.
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