Jiaxin He,Jialiang Li
Jiaxin He
Motivated by recent development of tensor regression modeling, we propose a novel tensor ensemble learning (TEL) approach. While CANDECOMP/PARAFAC (CP) decomposition is an efficient technique to reduce the number of parameters in tensor cov...
Confidence intervals and point estimates for treatment effects in adaptive enrichment designs [0.03%]
自适应富集设计中治疗效应的置信区间和点估计
Jinyu Zhu,Andrew Titman,Fang Wan
Jinyu Zhu
Adaptive enrichment designs allow subgroup selection of the patient population within a confirmatory trial via an interim analysis. However, this design complicates treatment effect estimation and uncertainty quantification. This paper intr...
Estimating conditional survival benefit for the allocation of scarce resources [0.03%]
估计条件生存效益以分配稀缺资源
Ilaria Prosepe,Nan van Geloven,Hans de Ferrante et al.
Ilaria Prosepe et al.
Whenever treatment is scarce, the question of how to allocate resources arises. One option is to allocate based on conditional survival benefit, defined as the contrast between an individual's expected survival with and without treatment. E...
Designing clinical trials for the comparison of single and multiple quantiles with right-censored data [0.03%]
基于右删失数据的分位数临床试验设计比较研究
Beatriz Farah,Olivier Bouaziz,Aurélien Latouche
Beatriz Farah
Based on the test for equality of quantiles originally introduced by Kosorok (1999), we propose new power formulas for the comparison of one quantile between two treatment groups, as well as for the comparison of a collection of quantiles. ...
Rank-based methods for assessing equivalence/non-inferiority with assay sensitivity in a three-arm trial with ordinal endpoints [0.03%]
秩和检验在有序数据三臂临床试验等效性和非劣效性评价中的应用研究
Shi-Fang Qiu,Dai-Min Li,Wai-Yin Poon
Shi-Fang Qiu
Various approaches have been developed to assess equivalence/non-inferiority with assay sensitivity in a three-arm trial with continuous or discrete endpoints. However, there is little work done on ordinal endpoints. Ordinal data do not hav...
A hybrid prior Bayesian method for combining domestic real-world data and overseas data in global drug development [0.03%]
一种混合先验贝叶斯方法，用于在药物全球开发中结合国内真实世界数据和海外数据
Keer Chen,Zengyue Zheng,Pengfei Zhu et al.
Keer Chen et al.
BackgroundHybrid clinical trial design integrates traditional randomized controlled trials (RCTs) with real-world data (RWD), aiming to enhance trial efficiency through dynamic incorporation of external data (External trial data and RWD). H...
Monitoring time to event in registry data using CUSUMs based on relative survival models [0.03%]
基于相对生存模型的CUSUM在注册数据中监测事件发生时间
Jimmy Huy Tran,Jan Terje Kvaløy,Hartwig Kørner
Jimmy Huy Tran
An aspect of interest in surveillance of diseases is whether the survival time distribution changes over time. By following data in health registries over time, this can be monitored, either in real time or retrospectively. With relevant ri...
A non-proportional hazards cure model with an application to gastric cancer data analysis [0.03%]
一个非比例风险治愈模型及其在胃癌数据分析中的应用
N Balakrishnan,M Mar Fenoy,M Carmen Pardo
N Balakrishnan
In many practical situations, some subjects may never experience the event of interest in their lifetime. These subjects are referred to as the cured or non-susceptible subjects. In the context of chronic disease treatment, this is referred...
Statistical methods for clustered competing risk data when the event types are only available in a training dataset [0.03%]
训练数据集中的事件类型可用时聚类竞争风险数据的统计方法
Yujie Wu,Ce Yang,Molin Wang
Yujie Wu
We develop methods to analyze clustered competing risks data when the event types are only available in a training dataset and are missing in the main study. We propose to estimate the exposure effects through the cause-specific proportiona...
Bayesian feature selection in joint models with application to a cardiovascular disease cohort study [0.03%]
联合模型中的贝叶斯特征选择及其在心血管疾病队列研究中的应用
Mirajul Islam,Michael J Daniels,Zeynab Aghabazaz et al.
Mirajul Islam et al.
Cardiovascular disease (CVD) cohorts collect data longitudinally to study the association between CVD risk factors and event times. An important area of scientific research is to better understand what features of CVD risk factor trajectori...