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Laplace regression with censored data

✍ Scribed by Matteo Bottai; Jiajia Zhang

Publisher: John Wiley and Sons
Year: 2010
Tongue: English
Weight: 319 KB
Volume: 52
Category: Article
ISSN: 0323-3847
DOI: 10.1002/bimj.200900310

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✦ Synopsis

Abstract

We consider a regression model where the error term is assumed to follow a type of asymmetric Laplace distribution. We explore its use in the estimation of conditional quantiles of a continuous outcome variable given a set of covariates in the presence of random censoring. Censoring may depend on covariates. Estimation of the regression coefficients is carried out by maximizing a non‐differentiable likelihood function. In the scenarios considered in a simulation study, the Laplace estimator showed correct coverage and shorter computation time than the alternative methods considered, some of which occasionally failed to converge. We illustrate the use of Laplace regression with an application to survival time in patients with small cell lung cancer.

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