# Model Based Bootstrap Methods for Interval Censored Data

arXiv: https://arxiv.org/abs/1312.6341 · HTML: https://mlsanity.com/paper/1312.6341/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Dec 2013.

## Built on by (most cited first, 1 of 1)

- [Neural interval-censored survival regression with feature selection](https://mlsanity.com/paper/2206.06885/) (2022)

## Abstract (arXiv)

We investigate the performance of model based bootstrap methods for constructing point-wise confidence intervals around the survival function with interval censored data. We show that bootstrapping from the nonparametric maximum likelihood estimator of the survival function is inconsistent for both the current status and case 2 interval censoring models. A model based smoothed bootstrap procedure is proposed and shown to be consistent. In addition, simulation studies are conducted to illustrate the (in)-consistency of the bootstrap methods. Our conclusions in the interval censoring model would extend more generally to estimators in regression models that exhibit non-standard rates of convergence.