A Bayesian model for spatial partly interval-censored data. (English) Zbl 07632281
Summary: Partly interval-censored data often occur in cancer clinical trials and have been analyzed as right-censored data. Patients’ geographic information sometimes is also available and can be useful in testing treatment effects and predicting survivorship. We propose a Bayesian semiparametric method for analyzing partly interval-censored data with areal spatial information under the proportional hazards model. A simulation study is conducted to compare the performance of the proposed method with the main method currently available in the literature and the traditional Cox proportional hazards model for right-censored data. The method is illustrated through a leukemia survival data set and a dental health data set. The proposed method will be especially useful for analyzing progression-free survival in multi-regional cancer clinical trials.
MSC:
| 62-XX | Statistics |
Keywords:
Bayesian semiparametric; conditionally autoregressive prior; partly interval-censored data; proportional hazards model; spatial frailtyReferences:
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