Yue Wang,Bin Nan,Daniel L Gillen et al.
Yue Wang et al.
We consider a new nonparametric method for analyzing the onset of a chronic condition, e.g., dementia, when death occurs frequently in the study population. In contrast to the commonly used semi-competing risks or illness-death model, we st...
Interim analysis in sequential multiple assignment randomized trials for survival outcomes [0.03%]
序贯多水平随机嵌入试验的中期分析及其生存结局研究
Zi Wang,Yu Cheng,Abdus S Wahed
Zi Wang
Sequential multiple assignment randomized trials (SMARTs) mimic the actual treatment processes experienced by physicians and patients in clinical settings and inform the comparative effectiveness of dynamic treatment regimes. In such trials...
Fast penalized generalized estimating equations for large longitudinal functional datasets [0.03%]
大型纵向功能数据集的快速惩罚广义估计方程
Gabriel Loewinger,Alexander W Levis,Erjia Cui et al.
Gabriel Loewinger et al.
Longitudinal binary or count functional data are common in neuroscience, but are often too large to analyze with existing functional regression methods. We propose one-step penalized generalized estimating equations that support generalized...
Justin M Clark,Kollin W Rott,James S Hodges et al.
Justin M Clark et al.
Recent work has made important contributions to the development of causally-interpretable meta-analysis. These methods transport treatment effects estimated in a collection of randomized trials to a target population of interest. Ideally, e...
Statistical inference for mean function of partially observed functional time series [0.03%]
部分观察到的功能时间序列的均值函数统计推断
Shuang Sun,Leheng Cai,Qirui Hu
Shuang Sun
We develop a statistical framework of inference for mean functions of partially observed functional time series. In the ideal case where curves are fully recorded during the observation period without noise, we establish the weak convergenc...
Subgroup identification via Interaction Tree and Mixed Model for Repeated Measures with application to Alzheimer's disease [0.03%]
基于交互树和重复测量混合模型的亚组识别及其在阿尔茨海默病研究中的应用
Zhichen Xu,Jimin Ding,Xiaogang Su et al.
Zhichen Xu et al.
In precision medicine, subgroup identification is crucial for designing personalized treatments. This research focuses on subgroup identification in longitudinal clinical trials by integrating the Interaction Tree (ITree) with the Mixed Mod...
Finite mixtures of linear quantile regressions with concomitant variables: a solution to endogeneity in longitudinal data modeling [0.03%]
带伴随变量的有限线性分位数回归混合模型：解决纵向数据建模中的内生性问题的一种方法
Marco Alfó,Maria Francesca Marino,Francesca Martella
Marco Alfó
Longitudinal studies give the chance to control for time-constant heterogeneity by adding unit-specific effects to the model formulation. When a random effect specification is adopted, issues of endogeneity may arise. We discuss quantile re...
A Bayesian phase I/II platform design with data augmentation accounting for delayed outcomes [0.03%]
一种基于数据增广的贝叶斯一期/二期平台设计用于延迟结果反应
Wentao Yang,Rongji Mu,Zhangsheng Yu
Wentao Yang
Delayed outcomes, such as late-onset toxicity and efficacy, present substantial challenges in dose optimization during Bayesian phase I/II platform trials for drug therapies across multiple indications. To address these challenges and ensur...
Rejoinder to the discussion on "INTACT: A method for integration of longitudinal physical activity data from multiple sources" [0.03%]
“INTACT：一种多源纵向体力活动数据集成方法”的讨论回函
Jingru Zhang,Erjia Cui,Hongzhe Li et al.
Jingru Zhang et al.
We thank the discussants for their insightful comments and suggestions. In this rejoinder, we clarify the scope of the INTACT framework and discuss several important extensions motivated by the discussion. We address issues related to model...