Nonparametric Inference for Rates with Censored Survival Data

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.

Nonparametric Bayesian Inference For Survival Data

This article introduces a new Bayesian approach to the analysis of right-censored survival data. The hazard rate of interest is modeled as a product of conditionally independent stochastic processes, corresponding to (1) a baseline hazard function, and (2) a regression function representing the temporal innuence of the covariates. These processes jump at times that form time-homogeneous Poisson...

Nonparametric Tree-Structured Modeling for Interval-Censored Survival Data

Survival analysis has been a major research area in statistics. In survival analysis, time to some event is usually the outcome variable. The objective of a survival study is to identify the relationship between treatments, risk factors or other covariates and the time to event. However, in a real clinical trial or longitudinal study, the exact time to event for each participant is not always k...

Bayesian Inference for Survival Data with Nonparametric Hazards and Vague

Statistical inference is reviewed for survival data applications with hazard models having one parameter per distinct failure time and using Jeffreys' (1961) vague priors. Distinction between a discrete hazard and a piecewise exponential model is made. Bayes estimators of survival probabilities ace derived. For a single sample and a discrete hazard, the Bayes estimator is shown to be larger tha...

Inference on Conditional Quantile Residual Life for Censored Survival Data