Optimizing Graphical Procedures for Multiplicity Control in a Confirmatory Clinical Trial via Deep Learning [0.03%]
基于深度学习的确认性临床试验多重性校正图型方法优化
Tianyu Zhan,Alan Hartford,Jian Kang et al.
Tianyu Zhan et al.
In confirmatory clinical trials, it has been proposed to use a simple iterative graphical approach to construct and perform intersection hypotheses tests with a weighted Bonferroni-type procedure to control Type I errors in the strong sense...
Quantifying Efficiency Gains of Innovative Designs of Two-Arm Vaccine Trials for COVID-19 Using an Epidemic Simulation Model [0.03%]
利用流行病仿真模型量化COVID-19的两臂疫苗试验的创新设计效率优势
Rob Johnson,Chris Jackson,Anne Presanis et al.
Rob Johnson et al.
Clinical trials of a vaccine during an epidemic face particular challenges, such as the pressure to identify an effective vaccine quickly to control the epidemic, and the effect that time-space-varying infection incidence has on the power o...
Guogen Shan,Ece Bayram,Jessica Z K Caldwell et al.
Guogen Shan et al.
Repeated data are increasingly collected in studies to investigate the trajectory of change in measurements over time. Determining a link between one repeated measurement with another that is considered as the biomarker for disease progress...
Michael J Grayling,Adrian P Mander,James M S Wason
Michael J Grayling
Bioequivalence (BE) studies are most often conducted as crossover trials, and therefore establishing their required sample size necessitates specification of the within-person variance. Given that this specification is often difficult in pr...
An empirical comparison of segmented and stochastic linear mixed effects models to estimate rapid disease progression in longitudinal biomarker studies [0.03%]
在纵向生物标志物研究中快速疾病进展的分段线性混合效应模型和随机线性混合效应模型的经验比较研究
Weiji Su,Emrah Gecili,Xia Wang et al.
Weiji Su et al.
Longitudinal studies of rapid disease progression often rely on noisy biomarkers; the underlying longitudinal process naturally varies between subjects and within an individual subject over time; the process can have substantial memory in t...
Statistical models for composite endpoints of death and non-fatal events: a review [0.03%]
死亡和非致命性事件的复合终点的统计模型：回顾
Lu Mao,KyungMann Kim
Lu Mao
The proper analysis of composite endpoints consisting of both death and non-fatal events is an intriguing and sometimes contentious topic. The current practice of analyzing time to the first event often draws criticisms for ignoring the une...
A comparative study of Bayesian optimal interval (BOIN) design with interval 3+3 (i3+3) design for phase I oncology dose-finding trials [0.03%]
贝叶斯最优区间(BOIN)设计与区间3+3(i3+3)设计在I期肿瘤剂量寻找试验中的比较研究
Yanhong Zhou,Ruobing Li,Fangrong Yan et al.
Yanhong Zhou et al.
Bayesian optimal interval (BOIN) design is a model-assisted phase I dose-finding design to find the maximum tolerated dose (MTD). The hallmark of the BOIN design is its concise decision rule - making the decision of dose escalation and de-e...
Rejoinder to Letter to the Editor "The Hazards of Period Specific and Weighted Hazard Ratios" [0.03%]
对《关于时期特定性和加权危险比的危害》的回应信之编辑回信
Ray S Lin,Ji Lin,Satrajit Roychoudhury et al.
Ray S Lin et al.
Jonathan W Bartlett,Tim P Morris,Mats J Stensrud et al.
Jonathan W Bartlett et al.
William R Zame,Ioana Bica,Cong Shen et al.
William R Zame et al.
The world is in the midst of a pandemic. We still know little about the disease COVID-19 or about the virus (SARS-CoV-2) that causes it. We do not have a vaccine or a treatment (aside from managing symptoms). We do not know if recovery from...