‘‘A note on Laplace regression with censored data’’.

Posterior Inference in Bayesian Quantile Regression with Asymmetric Laplace Likelihood

The paper discusses the asymptotic validity of posterior inference of pseudo-Bayesian quantile regression methods with complete or censored data when an asymmetric Laplace likelihood is used. The asymmetric Laplace likelihood has a special place in the Bayesian quantile regression framework because the usual quantile regression estimator can be derived as the maximum likelihood estimator under ...

A note on the comparison between Laplace and Sumudu transforms

Quantile regression for censored mixed-effects models with applications to HIV studies.

HIV RNA viral load measures are often subjected to some upper and lower detection limits depending on the quantification assays. Hence, the responses are either left or right censored. Linear/nonlinear mixed-effects models, with slight modifications to accommodate censoring, are routinely used to analyze this type of data. Usually, the inference procedures are based on normality (or elliptical ...

Testing Censoring Point Independence

Identification in censored regression analysis and hazard models of duration outcomes relies on the condition that censoring points are independent of latent outcomes, an assumption which may be questionable in many settings. This note proposes a test for this assumption based on a Kolmogorov-Smirnov-like test statistic comparing two different nonparametric estimators for the latent outcome cdf...

A Note On Self-Consistent Estimation of Censored Quantile Regression

Censored quantile regression has recently been studied under two major approaches: one is based on Portnoy (2003) that adopts self-consistent principle for handling censoring and the other one is based on Peng and Huang (2008) that utilizes the martingale structure of randomly censored data. Though numerical studies have suggested the close proximity between these two methods, their underlying ...