Bayesian Nonparametric Sensitivity Analysis of Multiple Test Procedures Under Dependence [0.03%]
基于相关性的多种检测程序的贝叶斯非参敏感性分析
George Karabatsos
George Karabatsos
This paper introduces a sensitivity analysis method for multiple testing procedures (MTPs) using marginal p $p$ -values. The method is based on the Dirichlet process (DP) prior distribution, specified to support the entire space of MTPs, w...
Multiple Contrast Tests for Count Data: Small Sample Approximations and Their Limitations [0.03%]
计数数据的多重对比检验：小样本逼近及其局限性
Mareen Pigorsch,Ludwig A Hothorn,Frank Konietschke
Mareen Pigorsch
Although count data are collected in many experiments, their analysis remains challenging, especially in small sample sizes. Until now, linear or generalized linear models in Poisson or Negative Binomial distributional families have often b...
Censoring and Competing Risks: Avoidable and Non-Avoidable Events. Comment to the Article "Hazards constitute key quantities for analysing, interpreting and understanding time-to-event data" by Beyersmann, Schmoor, and Schumacher [0.03%]
censoring和竞争风险：可避免事件与不可避免事件。对Beyersmann，Schmoor和Schumacher所著论文“分析、解释和理解生存数据的关键量是风险”一文的评论
Per Kragh Andersen
Per Kragh Andersen
It is argued that even though censoring and competing events, technically, play similar roles when estimating hazard functions, they are conceptually different and should be treated as such when interpreting time-to-event data. ...
Revisiting Hazard Ratios: Can We Define Causal Estimands for Time-Dependent Treatment Effects? [0.03%]
再次探讨风险比例：我们可以定义时间依赖性治疗效果的因果估计量吗？
Dominic Edelmann
Dominic Edelmann
In this paper, some aspects concerning the causal interpretation of hazard contrasts are revisited. It is first investigated, in which sense the hazard ratio constitutes a causal effect. It is demonstrated that the hazard ratio at a timepoi...
Bayesian Structure Learning for Graphical Models With Symmetry Constraints [0.03%]
具有对称约束的图形模型的贝叶斯结构学习
Qiong Li,Nanwei Wang,Xin Gao et al.
Qiong Li et al.
PAM50 gene expression profiling, a popular and widely used tool, is employed to identify and assess the functional relationships and pathways among genes in patients with breast cancer. Motivated by a study aimed at concurrently recovering ...
Evaluating Causal Effects on Time-to-Event Outcomes in an RCT in Oncology With Treatment Discontinuation [0.03%]
肿瘤学随机对照试验中具有治疗中断的时间至事件结局因果效应的评估
Veronica Ballerini,Björn Bornkamp,Fabrizia Mealli et al.
Veronica Ballerini et al.
In clinical trials, patients may discontinue treatments prematurely, breaking the initial randomization. In our motivating study, a randomized controlled trial in oncology, patients assigned the investigational treatment may discontinue it ...
The Locally Active-Controlled Optimal Design: Applications in Oncology Clinical Studies [0.03%]
局部活跃控制最优设计在肿瘤临床研究中的应用
Xiao Zhang,Gang Shen
Xiao Zhang
Antitumor activity in oncology clinical trials is typically assessed using overall survival (OS) or progression-free survival (PFS) endpoints, which are often imprecise and uninformative in small, noncomparative studies. The tumor growth in...
A New Approach to the Nonparametric Behrens-Fisher Problem With Compatible Confidence Intervals [0.03%]
一种新的非参数Behrens-Fisher问题的方法及其相容置信区间方法
Stephen Schüürhuis,Frank Konietschke,Edgar Brunner
Stephen Schüürhuis
We propose a new method to address the nonparametric Behrens-Fisher problem, allowing for unequal distribution functions across the two samples. The procedure tests the null hypothesis H 0 : θ = 1 / 2 $/mathcal {H}_0: /theta = /ni...
Intercept Estimation of Semi-Parametric Joint Models in the Context of Longitudinal Data Subject to Irregular Observations [0.03%]
纵向数据半参数联合模型下不规则观察下的截距估计问题研究
Luis Ledesma,Eleanor Pullenayegum
Luis Ledesma
Longitudinal data are often subject to irregular visiting times, with outcomes and visit times influenced by a latent variable. Semi-parametric joint models that account for this dependence have been proposed; among these, the Sun model is ...
Impact of Near-Positivity Violations on IPTW-Estimated Marginal Structural Survival Models With Time-Dependent Confounding [0.03%]
近 positivity 违约对基于时间依赖性混淆的时间加权边缘结构生存模型的影响
Marta Spreafico
Marta Spreafico
In longitudinal observational studies, marginal structural models (MSMs) are used to analyze the causal effect of an exposure on the (time-to-event) outcome of interest, while accounting for exposure-affected time-dependent confounding. In ...