A latent health process model for dynamic risk prediction with application to an HPV study [0.03%]
应用于HPV研究的动态风险预测潜在健康过程模型
Siddharth Roy,Anindya Roy,Megan A Clarke et al.
Siddharth Roy et al.
Individuals with an elevated risk of disease (ex., HPV infection) are often monitored with increased screening along with the collection of additional biomarkers to improve risk assessment at each screening visit. These individuals may expe...
Youngjin Cho,Pang Du
Youngjin Cho
Competing risks, referring to multiple mutually exclusive cause-specific events in survival data, are commonly seen in medical and engineering studies. In the presence of covariates, the Cox proportional hazards model is the most common app...
Computationally and statistically efficient estimation of time-smoothed counterfactual curves [0.03%]
高效估计时间平滑处理效应曲线的方法
Herbert P Susmann,Nicholas T Williams,Richard Liu et al.
Herbert P Susmann et al.
Longitudinal causal inference is concerned with defining, identifying, and estimating the effect of a time-varying intervention on a time-varying outcome that is indexed by a follow-up time. In an observational study, Robins's generalized g...
Backward joint model for the joint dynamic prediction of time-to-event and longitudinal data: basic formulation and new developments [0.03%]
时间到事件和纵向数据的联合动态预测的逆向联合模型：基本公式和最新发展
Wenhao Li,Shikun Wang,Zhe Yin et al.
Wenhao Li et al.
Dynamic prediction of future clinical outcomes based on longitudinally measured predictors plays a crucial role in disease management and patient counseling, particularly when conventional static models are inadequate. Joint modeling of lon...
Transition dynamics modeling of pre-trained accelerometry representations for time to diagnosis of Parkinson's disease [0.03%]
帕金森病诊断时间的预训练加速度计表示的过渡动态模型
Huiming Xie,Fei Xue,Xiao Wang
Huiming Xie
Early identification of Parkinson's disease is critical for timely intervention. Disruptions in sleep architecture and changes in physical activity patterns have been reported years before motor symptom onset, yet prodromal behavioral chang...
Causal effect on the number of life years lost due to a specific event: average treatment effect and variable importance [0.03%]
特定事件导致的寿命年损失的因果影响：平均处理效应和变量重要性
Simon Christoffer Ziersen,Torben Martinussen
Simon Christoffer Ziersen
Competing risk is a common phenomenon when dealing with time-to-event outcomes in biostatistical applications. An attractive estimand in this setting is the "number of life-years lost due to a specific cause of death". It provides a direct ...
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 [0.03%]
非参数估计在渐进性多状态模型中当前状态数据下的“过去”占用时间分布的条件下的状态进入时间分布的更正
Samuel Anyaso-Samuel,Somnath Datta
Samuel Anyaso-Samuel
Published Erratum
Lifetime data analysis. 2026 Jul 25;32(3):43. DOI:10.1007/s10985-026-09719-9 2026
Kolmogorov-Smirnov-type test for dependently double-truncated durations: A copula approach [0.03%]
基于相依双截断数据的Kolmogorov-Smirnov检验：一个Copula方法
Anne-Marie Toparkus,Rafael Weißbach
Anne-Marie Toparkus
Given a double-truncated sample of lifespans, we test the hypothesis of a parametric distribution family for the lifespan. Demography typically certifies the life expectancy to be nonstationary in time. We model the resulting dependence bet...
Threshold regression based on geometric Brownian motion with application to stock market prices [0.03%]
基于几何布朗运动的阈值回归及其在股票价格中的应用
Siwarak Sawongnam,Jiraphan Suntornchost
Siwarak Sawongnam
The threshold regression model, first introduced by Lee and Whitmore in 2006 by combining the concepts of the first hitting time model and linear regression, has been widely applied in the medical context. The model features enhanced capabi...
Shared frailty sieve estimation for dependent left truncated and interval censored data [0.03%]
依赖的左截断和区间删失数据下的共享脆弱性筛选估计方法
Muhammad Mustapha,Zarina Mohd Khalid
Muhammad Mustapha
Analysis of left-truncated and interval-censored survival data is challenging, particularly when the failure time and observation process are dependent. Existing methods, including Sun et al. (2023), model dependency via copulas, which may ...