A Bayesian model for spatial partly interval-censored data. Issue 12 (1st December 2022)

• Record Type: Journal Article
• Authors: Pan, Chun; Cai, Bo
• Is Part Of: Communications in statistics. Volume 51:Issue 12(2022)
• Page Start: 7513
• Page End: 7525
• Publication Date: 2022-12-01
• Subjects: Bayesian semiparametric -- Conditionally autoregressive prior -- Partly interval-censored data -- Proportional hazards model -- Spatial frailty; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2020.1839497
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract: 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.