Change point estimation in monitoring survival time: probability of the occurrence of the change point in the last {25, 50, 100, 200, 300, 400, 500} observations prior to signalling for RAST CUSUM

The dataset was collected to model change point estimation in time-to-event data for a clinical process with dichotomous outcomes, death and survival, where patient mix was present. Modelling was completed using a Bayesian framework. The performance of the Bayesian estimators was investigated through simulation in conjunction with RAST CUSUM control charts for monitoring right censored survival time of patients who underwent cardiac surgery procedures within a follow-up period of 30 days.

The dataset presents the probability of the occurrence of the change point in the last {25, 50, 100, 200, 300, 400, 500} observations prior to signalling for RAST CUSUM () where and .

本数据集的收集旨在对临床过程中具有二分类结果的生存时间数据中的变化点进行建模，其中存在患者混合情况。建模工作采用贝叶斯框架完成。通过模拟研究贝叶斯估计器的性能，并结合 RAST CUSUM 控制图（RAST CUSUM）对接受心脏手术并在30天随访期内进行监测的患者右端截尾生存时间进行监控。数据集展示了在发出 RAST CUSUM 信号前 {25, 50, 100, 200, 300, 400, 500} 个观测值中发生变化点的概率。