Multi-source analyses of average treatment effects with failure time outcomes [0.03%]
多数据源的治疗效果平均值分析与失效时间结果
Lan Wen,Jon A Steingrimsson,Sarah E Robertson et al.
Lan Wen et al.
Analyses of multi-source data, such as data from multi-center randomized trials, individual participant data meta-analyses, or pooled analyses of observational studies, combine information to estimate an overall average treatment effect. Ho...
Dongfeng Wu
Dongfeng Wu
A probability method to estimate cancer risk for asymptomatic individuals for the rest of life was developed based on one's current age and screening history using the disease progressive model. The risk is a function of the transition prob...
Seoyoon Cho,Matthew A Psioda,Joseph G Ibrahim
Seoyoon Cho
We propose a joint model for multiple time-to-event outcomes where the outcomes have a cure structure. When a subset of a population is not susceptible to an event of interest, traditional survival models cannot accommodate this type of phe...
Shape-constrained estimation for current duration data in cross-sectional studies [0.03%]
横截面数据下现行持续期的形状约束估计方法研究
Chi Wing Chu,Hok Kan Ling
Chi Wing Chu
We study shape-constrained nonparametric estimation of the underlying survival function in a cross-sectional study without follow-up. Assuming the rate of initiation event is stationary over time, the observed current duration becomes a len...
Design and analysis of individually randomized group-treatment trials with time to event outcomes [0.03%]
个体随机分组治疗试验的结构化设计与分析及结局指标的生存时间分析
Sin-Ho Jung
Sin-Ho Jung
In a typical individually randomized group-treatment (IRGT) trial, subjects are randomized between a control arm and an experimental arm. While the subjects randomized to the control arm are treated individually, those in the experimental a...
Investigating network structures in recurrent event data with discrete observation times [0.03%]
具有离散观测时间的递归事件数据中的网络结构研究
Yufeng Xia,Yangkuo Li,Xiaobing Zhao et al.
Yufeng Xia et al.
To investigate pairwise interactions arising from recurrent event processes in a longitudinal network, the framework of the stochastic block model is followed, where every node belongs to a latent group and interactions between node pairs f...
Regression analysis of a graphical proportional hazards model for informatively left-truncated current status data [0.03%]
一种图形比例危险模型的信息左截断当前状态数据的回归分析
Mengyue Zhang,Shishu Zhao,Shuying Wang et al.
Mengyue Zhang et al.
In survival analysis, researchers commonly focus on variable selection issues in real-world data, particularly when complex network structures exist among covariates. Additionally, due to factors such as data collection costs and delayed en...
Integrative analysis of high-dimensional RCT and RWD subject to censoring and hidden confounding [0.03%]
高维随机对照试验和真实世界数据的综合分析及其应对删失和隐藏混淆变量的方法
Xin Ye,Shu Yang,Xiaofei Wang et al.
Xin Ye et al.
In this study, we focus on estimating the heterogeneous treatment effect (HTE) for survival outcome. The outcome is subject to censoring and the number of covariates is high-dimensional. We utilize data from both the randomized controlled t...
Total time on test-based goodness-of-fit statistics for the reciprocal property in fatigue-life models [0.03%]
基于累计试验时间的拟合优度统计量及其在疲劳寿命模型中的应用
Cecilia Castro,Marta Azevedo,Víctor Leiva et al.
Cecilia Castro et al.
We propose a new goodness-of-fit procedure designed to verify the reciprocal property that characterizes the fatigue-life or Birnbaum-Saunders (BS) distribution. Under this property, scaling a random variable that takes positive values by i...
Robust inverse probability weighted estimators for doubly truncated Cox regression with closed-form standard errors [0.03%]
具有封闭形式标准误差的双重截断Cox回归的稳健逆概率加权估计器
Omar Vazquez,Sharon X Xie
Omar Vazquez
Survival data is doubly truncated when only participants who experience an event during a random interval are included in the sample. Existing methods typically correct for double truncation bias in Cox regression through inverse probabilit...