Generalized pairwise comparisons using pseudo-observations for time-to-event censored data in a randomized controlled trial setting [0.03%]
随机对照试验中使用伪观测值的广义配对比较时间结局 censoring 数据的方法研究
Stephanie Pan,Prasad Patil,Janice Weinberg et al.
Stephanie Pan et al.
Generalized pairwise comparison (GPC) methods are extensions of the Mann-Whitney approach that allow comparisons of outcomes through prioritized ranking, and they have been widely applied in randomized controlled trials (RCTs). Importantly,...
Heewon Park,Seiya Imoto,Satoru Miyano
Heewon Park
Heterogeneous gene networks capture coordinated gene activities and systemic disruptions in complex biological processes and diseases, but extracting biologically meaningful insights from these large-scale networks remains challenging due t...
Joint modeling of composite quantile regression for multiple ordinal longitudinal data with its applications to a dementia dataset [0.03%]
复合分位数回归的联合建模及其在痴呆症数据集中的应用
Shuqing Liang,Lina Bian,Qi Yang et al.
Shuqing Liang et al.
In the context of longitudinal data regression modeling, individuals often have two or more response indicators, and these response indicators are typically correlated to some extent. Additionally, in the field of clinical medicine, the res...
Grouped multi-trajectory modeling using finite mixtures of multivariate contaminated normal linear mixed model [0.03%]
基于多元污染正态线性混合模型的分组多轨迹建模
Tsung-I Lin,Wan-Lun Wang
Tsung-I Lin
There has been growing interest across various research domains in the modeling and clustering of multivariate longitudinal trajectories obtained from internally near-homogeneous subgroups. One prominent motivation for such work arises from...
Restricted mean survival time in cluster randomized trials with a small number of clusters: Improving variance estimation of the intervention effect from the pseudo-values regression [0.03%]
分组随机试验中限制均生存时间的应用：伪值回归法估计干预效应方差的改进（当试验的顶点个数较少时）
Floriane Le Vilain-Abraham,Solène Desmée,Jennifer A Thompson et al.
Floriane Le Vilain-Abraham et al.
In randomized clinical trials with a time-to-event outcome, the intervention effect could be quantified by a difference in restricted mean survival time (ΔRMST) between the intervention and control groups, defined as the expected survival ...
A two-stage joint modeling approach for multiple longitudinal markers and time-to-event data [0.03%]
一种用于多纵向标记物和生存时间数据的两阶段联合建模方法
Taban Baghfalaki,Reza Hashemi,Catherine Helmer et al.
Taban Baghfalaki et al.
Joint modeling of multiple longitudinal markers and time-to-event outcomes is common in clinical studies. However, as the number of markers increases, estimation becomes computationally challenging or infeasible due to long runtimes and con...
Fansheng Kong,Maozai Tian,Zhihao Wang et al.
Fansheng Kong et al.
When data become increasingly complex, desirable models are required to be more flexible for analyzing survival data. Building upon the existing functional Cox model, we introduce a novel functional varying-coefficient Cox model and the cor...
Joint model with latent disease age: Overcoming the need for reference time [0.03%]
隐性病程年龄的联合模型：克服对基准时刻的需求
Juliette Ortholand,Nicolas Gensollen,Stanley Durrleman et al.
Juliette Ortholand et al.
Heterogeneity of the progression of neurodegenerative diseases is one of the main challenges faced in developing therapies. Thanks to the increasing number of clinical databases, progression models have allowed a better understanding of thi...
Robust Emax model fitting: Addressing nonignorable missing binary outcome in dose-response analysis [0.03%]
稳健的EMAX模型拟合：解决剂量反应分析中缺失二元结果非缺失性问题
Jiangshan Zhang,Vivek Pradhan,Yuxi Zhao
Jiangshan Zhang
The Binary Emax model is widely employed in dose-response analysis during drug development, where missing data often pose significant challenges. Addressing nonignorable missing binary responses-where the likelihood of missing data is relat...
Dynamic prediction of death risk given a renewal hospitalization process [0.03%]
基于再入院过程的死亡风险动态预测模型研究
Telmo Pérez-Izquierdo,Irantzu Barrio,Cristobal Esteban
Telmo Pérez-Izquierdo
Predicting the risk of death for chronic patients is highly valuable for informed medical decision-making. This paper proposes a general framework for dynamic prediction of the risk of death of a patient given her hospitalization history. P...