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Lifetime Data Analysis

An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data

Lifetime Data Analysis OnlineFirst articles


Quantile regression-based Bayesian joint modeling analysis of longitudinal–survival data, with application to an AIDS cohort study

In longitudinal studies, it is of interest to investigate how repeatedly measured markers are associated with time to an event. Joint models have received increasing attention on analyzing such complex longitudinal–survival data with multiple data …


Semiparametric regression analysis of doubly censored failure time data from cohort studies

Doubly censored failure time data occur when the failure time of interest represents the elapsed time between two events, an initial event and a subsequent event, and the observations on both events may suffer censoring. A well-known example of …


Penalized full likelihood approach to variable selection for Cox’s regression model under nested case–control sampling

Assuming Cox’s regression model, we consider penalized full likelihood approach to conduct variable selection under nested case–control (NCC) sampling. Penalized non-parametric maximum likelihood estimates (PNPMLEs) are characterized by …


A causal proportional hazards estimator under homogeneous or heterogeneous selection in an IV setting

In this paper we present a framework to do estimation in a structural Cox model when there may be unobserved confounding. The model is phrased in terms of a selection bias function and a baseline model that describes how covariates affect the …


Landmark estimation of transition probabilities in non-Markov multi-state models with covariates

In non-Markov multi-state models, the traditional Aalen–Johansen (AJ) estimator for state transition probabilities is generally not valid. An alternative, suggested by Putter and Spitioni, is to analyse a subsample of the full data, consisting of …

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About this journal

Lifetime Data Analysis is the only journal dedicated to statistical methods and applications for lifetime data. The journal advances and promotes statistical science in various applied fields that deal with lifetime data, including actuarial science, economics, engineering, environmental sciences, management, medicine, operations research, public health, and social and behavioral sciences.

A partial list of topics reflecting the broad range of interests covered in the journal includes accelerated failure time models, degradation processes, meta-analysis, models for multiple events, nonparametric estimation of survival functions, quality-of-life models, rank tests for comparing lifetime distributions, and reliability methods.

Officially cited as:

Lifetime Data Anal

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