Bayesian inference on age-specific survival for censored and truncated data

Bayesian inference of Weibull distribution based on left truncated and right censored data

This article deals with the Bayesian inference of the unknown parameters of the Weibull distribution based on the left truncated and right censored data. It is assumed that the scale parameter of the Weibull distribution has a gamma prior. The shape parameter may be known or unknown. If the shape parameter is unknown, it is assumed that it has a very general log-concave prior distribution. When...

Likelihood Inference for Left Truncated and Right Censored Lifetime Data

Left truncation and right censoring arise naturally in lifetime data. Left truncation arises because in many situations, failure of a unit is observed only if it fails after a certain period. Often, the units under study may not be followed until all of them fail and the experimenter may have to stop at a certain time when some of the units may still be working. This introduces right censoring ...

Semiparametric likelihood inference for left-truncated and right-censored data.

This paper proposes a new estimation procedure for the survival time distribution with left-truncated and right-censored data, where the distribution of the truncation time is known up to a finite-dimensional parameter vector. The paper expands on the Vardis multiplicative censoring model (Vardi, 1989. Multiplicative censoring, renewal processes, deconvolution and decreasing density: non-parame...

Bayesian Perspective on Random Censored Survival Data

A unit is said to be randomly censored when the information on time occurrence of an event is not available due to either loss to followup, withdrawal, or nonoccurrence of the outcome event before the end of the study. It is assumed in independent random/noninformative censoring that each individual has his/her own failure time T and censoring time C; however, one can only observe the random ve...

Inference on Conditional Quantile Residual Life for Censored Survival Data