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

2016 - 2026

Current editor(s): Mei-Ling Ting Lee

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Volume 32, issue 3, 2026

A latent health process model for dynamic risk prediction with application to an HPV study pp. 1-24

Siddharth Roy, Anindya Roy, Megan A. Clarke, Ana Gradissimo, Robert D. Burk, Nicolas Wentzensen and Danping Liu

Variable selection in causal semiparametric transformation models with all-or-nothing treatment compliance pp. 1-47

Lijun Fang, Shuwei Li and Tao Hu

Correction to: A uniformisation-driven algorithm for inference-related estimation of a phase-type ageing model pp. 1-2

Boquan Cheng, Bruce Jones, Xiaoming Liu and Rogemar Mamon

Correction to: Nonparametric estimation of a state entry time distribution conditional on a “past” state occupation in a progressive multistate model with current status data pp. 1-2

Samuel Anyaso-Samuel and Somnath Datta

Correction to: Nonparametric estimation of conditional survival function with time-varying covariates using DeepONet pp. 1-2

Bingqing Hu and Bin Nan

Causal effect on the number of life years lost due to a specific event: average treatment effect and variable importance pp. 1-43

Simon Christoffer Ziersen and Torben Martinussen

Unobserved heterogeneity in threshold regression based on the hitting times of a reflected Brownian motion for recurrent hypoglycemia pp. 1-22

Yingfa Xie, Haoda Fu, Yuan Huang and Jun Yan

Backward joint model for the joint dynamic prediction of time-to-event and longitudinal data: basic formulation and new developments pp. 1-28

Wenhao Li, Shikun Wang, Zhe Yin, Brad C. Astor, Wei Yang, Tom H. Greene and Liang Li

Kolmogorov-Smirnov-type test for dependently double-truncated durations: A copula approach pp. 1-38

Anne-Marie Toparkus and Rafael Weißbach

Shared frailty sieve estimation for dependent left truncated and interval censored data pp. 1-21

Muhammad Mustapha and Zarina Mohd Khalid

Transition dynamics modeling of pre-trained accelerometry representations for time to diagnosis of Parkinson’s disease pp. 1-26

Huiming Xie, Fei Xue and Xiao Wang

Competing risk model with a nonparametric form of relative risks pp. 1-26

Youngjin Cho and Pang Du

Threshold regression based on geometric Brownian motion with application to stock market prices pp. 1-23

Siwarak Sawongnam and Jiraphan Suntornchost

Computationally and statistically efficient estimation of time-smoothed counterfactual curves pp. 1-23

Herbert P. Susmann, Nicholas T. Williams, Richard Liu, Jessica G. Young and Iván Díaz

Functional win-fractions regression models for composite outcomes pp. 1-37

Abhisek Chakraborty and Abhishek Mandal

Volume 32, issue 2, 2026

Doubly robust g-estimation of structural nested cumulative survival time models with non-ignorable, non-monotone missing data in time-varying confounders pp. 1-31

Yoshinori Takeuchi, Sho Komukai, Atsushi Goto and Tomohiro Shinozaki

Training-set conditionally valid prediction sets with right-censored data pp. 1-38

Wenwen Si and Hongxiang Qiu

Reduction techniques for survival analysis pp. 1-45

Johannes Piller, Léa Orsini, Simon Wiegrebe, Sophie Hanna Langbein, Lukas Burk, John Zobolas, Philip Studener, Markus Goeswein and Andreas Bender

Gradient boosting-based discrete failure time model for selecting time-varying effects and interactions pp. 1-28

Lingfeng Luo, Kevin He and Jeremy M. G. Taylor

Q-learning via deep learning-based Buckley–James method for non-linear censored data pp. 1-19

Jeongjin Lee and Jong-Min Kim

Kolmogorov–Smirnov and Cramér–von Mises tests for the k-sample problem with left-truncated and right-censored data pp. 1-32

Adrián Lago, Juan Carlos Pardo-Fernández and Jacobo de Uña-Álvarez

Nonparametric estimation of average effects of a continuous treatment for survival data with a cured fraction pp. 1-27

Hang Liu and Yingwei Peng

Variable selection with broken adaptive ridge regression for interval-censored competing risks data pp. 1-54

Fatemeh Mahmoudi, Chenxi Li, Kaida Cai and Xuewen Lu

Inference for cause-specific cox model absolute risk in cohort subsampling designs pp. 1-23

Lola Etiévant and Mitchell H. Gail

Instrumental variable estimation of a hazard ratio for treatment with a waiting time without specifying its dependence on unmeasured confounders: application to a procedural registry pp. 1-23

Todd A. MacKenzie, Pablo Martínez-Camblor, Haobin Chen, Jesse A. Columbo and A. James O’Malley

Nonparametric estimation of a state entry time distribution conditional on a “past” state occupation in a progressive multistate model with current status data pp. 1-26

Samuel Anyaso-Samuel and Somnath Datta

Estimating attributable risk functions for censored time-to-event in disease prevention research pp. 1-26

Ying Qing Chen, Yixin Wang, Xinyi Zhang and Ross L. Prentice

Comparing adaptive treatment strategies in two-stage randomized trials with grouped survival data pp. 1-20

Monique Sparkman, Susan Halabi and Zhiguo Li

Nonparametric estimation of conditional survival function with time-varying covariates using DeepONet pp. 1-16

Bingqing Hu and Bin Nan

The semi-competing risk problem revisited pp. 1-16

Ross L. Prentice and Aaron K. Aragaki

Semiparametric regression analysis of interval-censored competing risks data under additive hazards model with missing event types pp. 1-24

Ruobing Jia, Yichen Lou, Jianguo Sun and Peijie Wang

Optimal designs for discrete-time survival models with competing risks pp. 1-29

XiaoDong Zhou, YunJuan Wang, RongXian Yue and Weng Kee Wong

Partially linear Cox model with neural networks for left-truncated data pp. 1-18

Shiying Li, Li Shao and Shuwei Li

A dependent and censored first hitting-time model with compound Poisson processes pp. 1-25

Mikael Escobar-Bach, Alexandre Popier and Malo Sahin

Volume 32, issue 1, 2026

Estimation of the interpretable heterogeneous treatment effect with causal subgroup discovery in survival outcomes pp. 1-26

Na Bo and Ying Ding

On Multiple Time Scales and Collapsibility pp. 1-9

David Oakes

Wasserstein GAN-based estimation for conditional distribution function with current status data pp. 1-23

Wen Su, Changyu Liu, Guosheng Yin and Jian Huang

Integrating high-dimensional censored data under privacy constraints via localized computations pp. 1-22

Bingyao Huang, Yanyan Liu and Xin Ye

Continuously updated estimation of conditional hazard functions pp. 1-22

Daphné Aurouet and Valentin Patilea

Deep learning for the change-point Cox model with current status data pp. 1-22

Qiyue Huang, Anyin Feng, Qiang Wu and Xingwei Tong

Beyond Bonferroni: new multiple contrast tests for time-to-event data under non-proportional hazards pp. 1-19

Ina Dormuth, Carolin Herrmann, Frank Konietschke, Markus Pauly, Matthias Wirth and Marc Ditzhaus

Two-stage recurrent events random effects models pp. 1-28

Thomas Harder Scheike

Deep tobit model: an integrated framework for high-dimensional censored regression with variable selection pp. 1-28

Tong Wu, Jiawen Hu, Zhi-Sheng Ye and Nan Chen

Reliability and estimation of the zero-inflated transmuted geometric distribution with applications and actuarial insights pp. 1-29

Kalpasree Sharma, Partha Jyoti Hazarika, Mohamed S. Eliwa and Mahmoud El-Morshedy

A flexible copula model for bivariate survival data with dependent censoring pp. 1-18

Reuben Adatorwovor and Yinghao Pan

Confidence intervals for high-dimensional accelerated failure time models under measurement errors pp. 1-18

Qin Yu, Xin Zhou, Jia Zhou and Zemin Zheng

Robust functional Cox regression model pp. 1-39

Gizel Bakicierler Sezer and Ufuk Beyaztas

Generalized win-odds regression models for composite endpoints pp. 1-24

Bang Wang, Zi Wang and Yu Cheng

Bayesian semiparametric partially linear cure models with partly interval-censored data pp. 1-34

Yuyang Guo, Chunjie Wang and Xiaoyu Liu

Estimating treatment effects on duration with disease: a principal stratification framework pp. 1-17

Erik T. Parner