Simulating Data From Marginal Structural Models for a Survival Time Outcome [0.03%]
生成生存时间结果的边际结构模型的数据模拟
Shaun R Seaman,Ruth H Keogh
Shaun R Seaman
Marginal structural models (MSMs) are often used to estimate causal effects of treatments on survival time outcomes from observational data when time-dependent confounding may be present. They can be fitted using, for example, inverse proba...
Conditional Variable Screening for Ultra-High Dimensional Longitudinal Data With Time Interactions [0.03%]
具有时间交互的超高维纵向数据的条件变量筛选
Andrea Bratsberg,Abhik Ghosh,Magne Thoresen
Andrea Bratsberg
In recent years, we have been able to gather large amounts of genomic data at a fast rate, creating situations where the number of variables greatly exceeds the number of observations. In these situations, most models that can handle a mode...
Addressing Class Imbalance in Bayesian Classification Through Posterior Probability Adjustment [0.03%]
基于后验概率调整的贝叶斯分类中的类不平衡问题研究
Vahid Nassiri,Fetene Tekle,Kanaka Tatikola et al.
Vahid Nassiri et al.
Class imbalance is a known issue in classification tasks that can lead to predictive bias toward dominant classes. This paper introduces a novel straightforward Bayesian framework that adjusts posterior probabilities to counteract the bias ...
Jinmei Chen,Lixin Li,Yuhao Feng et al.
Jinmei Chen et al.
External data (e.g., real-world data (RWD) and historical data) have become more readily available. This has led to rapidly increasing interest in exploring and evaluating ways of utilizing external data to facilitate traditional clinical t...
Inverse-Weighted Quantile Regression With Partially Interval-Censored Data [0.03%]
带有部分区间检查数据的逆权量化回归
Yeji Kim,Taehwa Choi,Seohyeon Park et al.
Yeji Kim et al.
This paper introduces a novel approach to estimating censored quantile regression using inverse probability of censoring weighted (IPCW) methodology, specifically tailored for data sets featuring partially interval-censored data. Such data ...
Mixture Cure Semiparametric Accelerated Failure Time Models With Partly Interval-Censored Data [0.03%]
带有部分区间截断数据的混合愈合半参数加速失效时间模型
Isabel Li,Jun Ma,Benoit Liquet
Isabel Li
In practical survival analysis, the situation of no event for a patient can arise even after a long period of waiting time, which means a portion of the population may never experience the event of interest. Under this circumstance, one rem...
Charlotte Micheloud,Leonhard Held
Charlotte Micheloud
Replication studies are increasingly conducted to assess the credibility of scientific findings. Most of these replication attempts target studies with a superiority design, but there is a lack of methodology regarding the analysis of repli...
Cross-Cohort Mixture Analysis: A Data Integration Approach With Applications on Gestational Age and DNA-Methylation-Derived Gestational Age Acceleration Metrics [0.03%]
横断面混合分析：一种数据整合方法及其在胎龄和DNA甲基化衍生的胎龄加速指标方面的应用
Elena Colicino,Roberto Ascari,Hachem Saddiki et al.
Elena Colicino et al.
Data integration of multiple studies can provide enhanced exposure contrast and statistical power to examine associations between environmental exposure mixtures and health outcomes. Extant research has combined populations and identified a...
Estimating the Sampling Distribution of Posterior Decision Summaries in Bayesian Clinical Trials [0.03%]
贝叶斯临床试验中后验决策汇总的抽样分布估计
Shirin Golchi,James J Willard
Shirin Golchi
Bayesian inference and the use of posterior or posterior predictive probabilities for decision making have become increasingly popular in clinical trials. The current practice in Bayesian clinical trials relies on a hybrid Bayesian-frequent...
Group Integrative Dynamic Factor Models With Application to Multiple Subject Brain Connectivity [0.03%]
基于多受试者脑连接的组整合动态因子模型及其应用
Younghoon Kim,Zachary F Fisher,Vladas Pipiras
Younghoon Kim
This work introduces a novel framework for dynamic factor model-based group-level analysis of multiple subjects time-series data, called GRoup Integrative DYnamic factor (GRIDY) models. The framework identifies and characterizes intersubjec...