Assessing delayed treatment benefits of immunotherapy using long-term average hazard: a novel test/estimation approach [0.03%]
利用长期平均危险度评估免疫治疗的延迟疗效益处：一种新型检验/估计方法
Miki Horiguchi,Lu Tian,Kenneth L Kehl et al.
Miki Horiguchi et al.
Delayed treatment effects on time-to-event outcomes are commonly observed in randomized controlled trials of cancer immunotherapies. When the treatment effect has a delayed onset, the conventional test/estimation approach-using the log-rank...
Bayesian joint models for longitudinal, recurrent, and terminal event data [0.03%]
基于纵向、复发和终末事件数据的贝叶斯联合建模方法研究
Emily M Damone,Matthew A Psioda,Joseph G Ibrahim
Emily M Damone
Many methods exist to jointly model either recurrent and related terminal survival events or longitudinal outcome measures and related terminal survival event. However, few methods exist which can account for the dependency between all thre...
Bayesian generalized method of moments applied to pseudo-observations in survival analysis [0.03%]
贝叶斯广义矩法在生存分析伪观测值中的应用
Léa Orsini,Caroline Brard,Emmanuel Lesaffre et al.
Léa Orsini et al.
Bayesian inference for survival regression modeling offers numerous advantages, especially for decision-making and external data borrowing, but demands the specification of the baseline hazard function, which may be a challenging task. We p...
Pseudo-observations and super learner for the estimation of the restricted mean survival time [0.03%]
限制均值生存时间的估计中的伪观测值和超级学习器方法
Ariane Cwiling,Vittorio Perduca,Olivier Bouaziz
Ariane Cwiling
In the context of right-censored data, we study the problem of predicting the restricted time to event based on a set of covariates. Under a quadratic loss, this problem is equivalent to estimating the conditional restricted mean survival t...
Bayesian joint analysis of longitudinal data and interval-censored failure time data [0.03%]
纵向数据与区间删失生存数据的贝叶斯联合分析方法研究
Yuchen Mao,Lianming Wang,Xuemei Sui
Yuchen Mao
Joint modeling of longitudinal responses and survival time has gained great attention in statistics literature over the last few decades. Most existing works focus on joint analysis of longitudinal data and right-censored data. In this arti...
Causal effect estimation on restricted mean survival time under case-cohort design via propensity score stratification [0.03%]
基于倾向得分分层的病例队列设计中受限平均生存时间的因果效应估计方法研究
Wei-En Lu,Ai Ni
Wei-En Lu
In large observational studies with survival outcome and low event rates, the case-cohort design is commonly used to reduce the cost associated with covariate measurement. The restricted mean survival time (RMST) difference has been increas...
Wild bootstrap for counting process-based statistics: a martingale theory-based approach [0.03%]
基于鞅理论的计数过程统计量的野引导方法
Marina T Dietrich,Dennis Dobler,Mathisca C M de Gunst
Marina T Dietrich
The wild bootstrap is a popular resampling method in the context of time-to-event data analysis. Previous works established the large sample properties of it for applications to different estimators and test statistics. It can be used to ju...
Estimation and variable selection for semiparametric transformation models with length-biased survival data [0.03%]
加性乘积变换模型中带偏生存数据的估计和变量选择方法研究
Jih-Chang Yu,Yu-Jen Cheng
Jih-Chang Yu
In this study, we investigate estimation and variable selection for semiparametric transformation models with length-biased survival data-a special case of left truncation commonly encountered in the social sciences and cancer prevention tr...
Simultaneous clustering and joint modeling of multivariate binary longitudinal and time-to-event data [0.03%]
多元二值纵向数据和时间到事件数据的同步聚类和联合建模
Srijan Chattopadhyay,Sevantee Basu,Swapnaneel Bhattacharyya et al.
Srijan Chattopadhyay et al.
Joint modeling of longitudinal outcomes and time-to-event data has been extensively used in medical studies because it can simultaneously model the longitudinal trajectories and assess their effects on the event-time. However, in many appli...
Analysis of interval censored survival data in sequential multiple assignment randomized trials [0.03%]
序贯多重赋值随机化试验中区间审查生存数据的分析方法研究
Zhiguo Li
Zhiguo Li
Data analysis methods have been well developed for analyzing data to make inferences about adaptive treatment strategies in sequential multiple assignment randomized trials (SMART), when data are continuous or right-censored. However, in so...