Date of Award
Open Access Dissertation
Epidemiology and Biostatistics
Interval-censored time-to-event data occur naturally in studies of diseases where the symptoms are not directly observable, and periodic clinical examinations are required for detection. Due to the lack of well-established procedures, interval-censored data have been conventionally treated as right-censored data, however, this introduces bias at the first place. This dissertation focuses on methodological research and software development for interval-censored data. Specifically, it consists of three projects. The first project is to create an R package for regression analysis and survival curve estimation of interval-censored data based on several published papers by our research team. In the second project, a Bayesian semiparametric proportional hazards model with spatial random effect is developed for spatially correlated interval-censored data. In the third project, we propose a multivariate frailty model for clustered interval-censored failure times, which is analogous to a mixed model in regression analysis.
Pan, C.(2013). Models and Software Development For Interval-Censored Data. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/2303