Change point estimation in monitoring survival time: posterior estimates of step change point model parameters
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 posterior estimates (mode, sd.) of step change point model parameters ( and ) following signals (RL) from RAST CUSUM () where and .
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