Estimation of Survival Function and Median Survival Time in Interval-Censored Data

Smooth estimation of the survival function for interval censored data.

Interval censored data arise naturally in large-scale panel studies where subjects can only be followed periodically and the event of interest can only be observed in some time intervals. To estimate the survival function the non-parametric maximum likelihood estimator (NPMLE) is commonly used, which is a step function having some large jumps. However, in many applications the underlying surviv...

Inferences on Median Failure Time for Censored Survival Data

Spatial Modeling of Censored Survival Data

An important issue in survival data analysis is the identification of risk factors. Some of these factors are identifiable and explainable by presence of some covariates in the Cox proportional hazard model, while the others are unidentifiable or even immeasurable. Spatial correlation of censored survival data is one of these sources that are rarely considered in the literatures. In this paper,...

Bayesian analysis and model selection for interval-censored survival data.

Interval-censored data occur in survival analysis when the survival time of each patient is only known to be within an interval and these censoring intervals differ from patient to patient. For such data, we present some Bayesian discretized semiparametric models, incorporating proportional and nonproportional hazards structures, along with associated statistical analyses and tools for model se...

Nonparametric regression with censored survival time data

The paper deals with a class of nonparametric regression estimates introduced by Beran (1981) to estimate conditional survival functions in the presence of right censoring. Weak convergence results are established for kernel and nearest neighbour estimates of the conditional cumulative hazard and survival functions as well as the quantile and L-type regression functionals.