Skip to main content

Lifetime Data Analysis OnlineFirst articles

Open Access 15-02-2024

The built-in selection bias of hazard ratios formalized using structural causal models

It is known that the hazard ratio lacks a useful causal interpretation. Even for data from a randomized controlled trial, the hazard ratio suffers from so-called built-in selection bias as, over time, the individuals at risk among the exposed and …

Richard A. J. Post, Edwin R. van den Heuvel, Hein Putter


Quantile difference estimation with censoring indicators missing at random

In this paper, we define estimators of distribution functions when the data are right-censored and the censoring indicators are missing at random, and establish their strong representations and asymptotic normality. Besides, based on empirical …

Cui-Juan Kong, Han-Ying Liang


A Bayesian proportional hazards mixture cure model for interval-censored data

The proportional hazards mixture cure model is a popular analysis method for survival data where a subgroup of patients are cured. When the data are interval-censored, the estimation of this model is challenging due to its complex data structure.

Chun Pan, Bo Cai, Xuemei Sui


Efficiency of the Breslow estimator in semiparametric transformation models

Semiparametric transformation models for failure time data consist of a parametric regression component and an unspecified cumulative baseline hazard. The nonparametric maximum likelihood estimator (NPMLE) of the cumulative baseline hazard can be …

Theresa P. Devasia, Alexander Tsodikov


Bias reduction for semi-competing risks frailty model with rare events: application to a chronic kidney disease cohort study in South Korea

In a semi-competing risks model in which a terminal event censors a non-terminal event but not vice versa, the conventional method can predict clinical outcomes by maximizing likelihood estimation. However, this method can produce unreliable or …

Jayoun Kim, Boram Jeong, Il Do Ha, Kook-Hwan Oh, Ji Yong Jung, Jong Cheol Jeong, Donghwan Lee