Within-trial data borrowing for sequential multiple assignment randomized trials [0.03%]
序贯多分组随机临床试验中同一试验数据借用的方法研究
Ales Kotalik,David M Vock,Nancy E Sherwood et al.
Ales Kotalik et al.
The Sequential Multiple Assignment Randomized Trial (SMART) is a complex trial design that involves randomizing a single participant multiple times in a sequential manner. This results in the branching nature of a SMART, which represents se...
Estimation and inference for causal spillover effects in egocentric-network randomized trials in the presence of network membership misclassification [0.03%]
存在网络成员分类错误的情况下，同伴网络随机试验中因果溢出效应的估计与推断
Ariel Chao,Donna Spiegelman,Ashley Buchanan et al.
Ariel Chao et al.
To leverage peer influence and increase population behavioral changes, behavioral interventions often rely on peer-based strategies. A common study design that assesses such strategies is the egocentric-network randomized trial (ENRT), wher...
Semiparametric mixture regression for asynchronous longitudinal data using multivariate functional principal component analysis [0.03%]
基于多变量函数主成分分析的异步纵向数据半参数混合回归模型
Ruihan Lu,Yehua Li,Weixin Yao
Ruihan Lu
The transitional phase of menopause induces significant hormonal fluctuations, exerting a profound influence on the long-term well-being of women. In an extensive longitudinal investigation of women's health during mid-life and beyond, know...
Penalized likelihood optimization for censored missing value imputation in proteomics [0.03%]
蛋白质组学中截尾缺失值插补的惩罚似然优化方法
Lucas Etourneau,Laura Fancello,Samuel Wieczorek et al.
Lucas Etourneau et al.
Label-free bottom-up proteomics using mass spectrometry and liquid chromatography has long been established as one of the most popular high-throughput analysis workflows for proteome characterization. However, it produces data hindered by c...
Random forest for dynamic risk prediction of recurrent events: a pseudo-observation approach [0.03%]
基于伪观察法的随机森林动态复发事件风险预测模型
Abigail Loe,Susan Murray,Zhenke Wu
Abigail Loe
Recurrent events are common in clinical, healthcare, social, and behavioral studies, yet methods for dynamic risk prediction of these events are limited. To overcome some long-standing challenges in analyzing censored recurrent event data, ...
Yixi Xu,Yi Zhao
Yixi Xu
This study introduces a mediation analysis framework when the mediator is a graph. A Gaussian covariance graph model is assumed for graph presentation. Causal estimands and assumptions are discussed under this presentation. With a covarianc...
Covariate-adjusted estimators of diagnostic accuracy in randomized trials [0.03%]
在随机试验中调整协变量的诊断准确性估计器
Jon A Steingrimsson
Jon A Steingrimsson
Randomized controlled trials evaluating the diagnostic accuracy of a marker frequently collect information on baseline covariates in addition to information on the marker and the reference standard. However, standard estimators of sensitivi...
Unlocking the power of time-since-infection models: data augmentation for improved instantaneous reproduction number estimation [0.03%]
感染后时间模型的力量解锁：数据扩充以提高瞬时再生数估计的准确性
Jiasheng Shi,Yizhao Zhou,Jing Huang
Jiasheng Shi
The time-since-infection (TSI) models, which use disease surveillance data to model infectious diseases, have become increasingly popular due to their flexibility and capacity to address complex disease control questions. However, a notable...
Scalable randomized kernel methods for multiview data integration and prediction with application to Coronavirus disease [0.03%]
可扩展的随机核方法用于多视角数据整合与预测以及冠状病毒疾病的实现
Sandra E Safo,Han Lu
Sandra E Safo
There is still more to learn about the pathobiology of coronavirus disease (COVID-19) despite 4 years of the pandemic. A multiomics approach offers a comprehensive view of the disease and has the potential to yield deeper insight into the p...
Understanding the opioid syndemic in North Carolina: A novel approach to modeling and identifying factors [0.03%]
理解北卡罗来纳州阿片类药物大流行：一种新颖的建模和识别因素的方法
Eva Murphy,David Kline,Kathleen L Egan et al.
Eva Murphy et al.
The opioid epidemic is a significant public health challenge in North Carolina, but limited data restrict our understanding of its complexity. Examining trends and relationships among different outcomes believed to reflect opioid misuse pro...