Choosing a reliability inspection plan for interval censored data

Turnbull’s Nonparametric Estimator for Interval-Censored Data

In most applications, the data may be interval-censored. By interval-censored data, we mean that a random variable of interest is known only to lie in an interval, instead of being observed exactly. In such cases, the only information we have for each individual is that their event time falls in an interval, but the exact time is unknown. A nonparametric estimate of the survival function can al...

Non-Bayesian Estimation and Prediction under Weibull Interval Censored Data

In this paper, a one-sample point predictor of the random variable X is studied. X is the occurrence of an event in any successive visits $L_i$ and $R_i$ :i=1,2…,n (interval censoring). Our proposed method is based on finding the expected value of the conditional distribution of X given $L_i$ and $R_i$ (i=1,2…,n). To make the desired prediction, our approach is on the basis of approximating the...

A multiple imputation approach for clustered interval-censored survival data.

Multivariate interval-censored failure time data arise commonly in many studies of epidemiology and biomedicine. Analysis of these type of data is more challenging than the right-censored data. We propose a simple multiple imputation strategy to recover the order of occurrences based on the interval-censored event times using a conditional predictive distribution function derived from a paramet...

A Bayesian Semiparametri AFT Model for Interval Censored Data

A Cox-Aalen model for interval-censored data

The Cox-Aalen model, obtained by replacing the baseline hazard function in the well-known Cox model with a covariate-dependent Aalen model, allows for both fixed and dynamic covariate effects. In this paper, we examine maximum likelihood estimation for a Cox-Aalen model based on interval-censored failure times with fixed covariates. The resulting estimator globally converges to the truth slower...