A method for determining groups in cumulative incidence curves in competing risk data [0.03%]
竞争风险数据中累积发病率曲线群体确定的方法
Marta Sestelo,Luís Meira-Machado,Nora M Villanueva et al.
Marta Sestelo et al.
The cumulative incidence function is the standard method for estimating the marginal probability of a given event in the presence of competing risks. One basic but important goal in the analysis of competing risk data is the comparison of t...
Gregor Buch,Andreas Schulz,Irene Schmidtmann et al.
Gregor Buch et al.
Many data sets exhibit a natural group structure due to contextual similarities or high correlations of variables, such as lipid markers that are interrelated based on biochemical principles. Knowledge of such groupings can be used through ...
Comparative review of novel model-assisted designs for phase I/II clinical trials [0.03%]
新型I/II期临床试验辅助设计的比较研究
Haolun Shi,Ruitao Lin,Xiaolei Lin
Haolun Shi
In recent years, both model-based and model-assisted designs have emerged to efficiently determine the optimal biological dose (OBD) in phase I/II trials for immunotherapy and targeted cellular agents. Model-based designs necessitate repeat...
Modeling tropical tuna shifts: An inflated power logit regression approach [0.03%]
热带金枪鱼转移的建模方法：膨胀权衡逻辑回归法
Francisco F Queiroz,Silvia L P Ferrari
Francisco F Queiroz
We introduce a new class of zero-or-one inflated power logit (IPL) regression models, which serve as a versatile tool for analyzing bounded continuous data with observations at a boundary. These models are applied to explore the effects of ...
A novel nonparametric time-dependent precision-recall curve estimator for right-censored survival data [0.03%]
一种新的非参数时间依赖精确召回率估计方法及其在生存分析右删失数据中的应用研究
Kassu Mehari Beyene,Ding-Geng Chen,Yehenew Getachew Kifle
Kassu Mehari Beyene
In order to assess prognostic risk for individuals in precision health research, risk prediction models are increasingly used, in which statistical models are used to estimate the risk of future outcomes based on clinical and nonclinical ch...
On repeated diagnostic testing in screening for a medical condition: How often should the diagnostic test be repeated? [0.03%]
重复诊断检测在医学筛查中的应用：诊断检测应如何频繁地进行重复？
Patarawan Sangnawakij,Dankmar Böhning
Patarawan Sangnawakij
In screening large populations a diagnostic test is frequently used repeatedly. An example is screening for bowel cancer using the fecal occult blood test (FOBT) on several occasions such as at 3 or 6 days. The question that is addressed he...
Recoverability and estimation of causal effects under typical multivariable missingness mechanisms [0.03%]
典型多变量缺失机制下的因果效应的可恢复性与估计问题
Jiaxin Zhang,S Ghazaleh Dashti,John B Carlin et al.
Jiaxin Zhang et al.
In the context of missing data, the identifiability or "recoverability" of the average causal effect (ACE) depends not only on the usual causal assumptions but also on missingness assumptions that can be depicted by adding variable-specific...
Lasse Fischer,Marta Bofill Roig,Werner Brannath
Lasse Fischer
In this paper, we consider online multiple testing with familywise error rate (FWER) control, where the probability of committing at least one type I error will remain under control while testing a possibly infinite sequence of hypotheses o...
Sharing information across patient subgroups to draw conclusions from sparse treatment networks [0.03%]
利用稀疏治疗网络在患者亚群间共享信息以得出结论
Theodoros Evrenoglou,Silvia Metelli,Johannes-Schneider Thomas et al.
Theodoros Evrenoglou et al.
Network meta-analysis (NMA) usually provides estimates of the relative effects with the highest possible precision. However, sparse networks with few available studies and limited direct evidence can arise, threatening the robustness and re...
Anna Pöhlmann,Edgar Brunner,Frank Konietschke
Anna Pöhlmann
Rank methods are well-established tools for comparing two or multiple (independent) groups. Statistical planning methods for the computing the required sample size(s) to detect a specific alternative with predefined power are lacking. In th...