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

From Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

Access Statistics for this journal.
Is something missing from the series or not right? See the RePEc data check for the archive and series.

Volume 32, issue 4, 2026

Nonparametric maximum likelihood estimation for competing risks frailty models pp. 1-33

Chew-Seng Chee, Il Do Ha, Youngjo Lee and Hangbin Lee

R-estimation with right-censored data pp. 1-43

Glen A. Satten, Mo Li, Ni Zhao and Robert L. Strawderman

Gradient boosting machine for survival prediction in studies with general failure-time outcome-dependent sampling design pp. 1-19

Haolin Li, Haibo Zhou and Jianwen Cai

Shape-constrained semiparametric maximum likelihood for backward time under an accelerated failure time model pp. 1-27

Jing Qin

Dynamic risk assessment by landmark modeling of the restricted residual mean survival time pp. 1-23

Yuan Zhang and Douglas E. Schaubel

No cure for cure models: killed by competing risks pp. 1-18

Hein Putter and Per Kragh Andersen

Estimating heterogeneous treatment effects with survival outcomes via a deep survival learner pp. 1-24

Yuming Sun, Jian Kang and Yi Li

Restricted mean time lost ratio regression: percentage of restricted mean time lost due to specific cause pp. 1-31

Thomas Scheike and Shiro Tanaka

Volume 32, issue 3, 2026

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

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

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

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

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

Anne-Marie Toparkus and Rafael Weißbach

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

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

Muhammad Mustapha and Zarina Mohd Khalid

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

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

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

Abhisek Chakraborty and Abhishek Mandal

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

Lijun Fang, Shuwei Li and Tao Hu

Volume 32, issue 2, 2026

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

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

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

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

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

Wenwen Si and Hongxiang Qiu

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

Mikael Escobar-Bach, Alexandre Popier and Malo Sahin

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

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

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

Hang Liu and Yingwei Peng

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

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

Shiying Li, Li Shao and Shuwei Li

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

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

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

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

Volume 32, issue 1, 2026

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

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

Yuyang Guo, Chunjie Wang and Xiaoyu Liu

On Multiple Time Scales and Collapsibility pp. 1-9

David Oakes

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

Na Bo and Ying Ding

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

Erik T. Parner

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

Bang Wang, Zi Wang and Yu Cheng

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

Wen Su, Changyu Liu, Guosheng Yin and Jian Huang

Robust functional Cox regression model pp. 1-39

Gizel Bakicierler Sezer and Ufuk Beyaztas

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

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

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