Bayesian Joint Modeling for Longitudinal Magnitude Data With Informative Dropout: An Application to Critical Care Data [0.03%]
具有信息缺失的纵向数据的贝叶斯联合模型：重症监护数据的应用
Wen Teng,Niall D Ferguson,Ewan C Goligher et al.
Wen Teng et al.
In various biomedical studies, analysis often focuses on data magnitudes, particularly when algebraic signs are irrelevant or lost. For repeated measures studies involving magnitude outcomes, incorporating random effects is essential as the...
Modeling Temporal Relationships Between Multivariate Repeated Markers Along With Clinical Endpoints: Application to Alzheimer's Disease and Related Dementias [0.03%]
用于阿尔茨海默病及相关痴呆症的多变量重复标志物与临床结果之间的时间关系建模
Anaïs Rouanet,Viviane Philipps,Bachirou O Taddé et al.
Anaïs Rouanet et al.
Diseases often involve multiple dimensions of interrelated impairments. Although significant advances have been made in joint models to simultaneously assess these processes in relation to clinical endpoints, they often fail to evaluate how...
Data Analysis Planning and Reporting for Confirmatory Multi-Lab Preclinical Trials: A Tutorial [0.03%]
确认性多实验室临床前试验的数据分析规划与报告教程
María Arroyo-Araujo,Clarissa F D Carneiro,Sophie K Piper et al.
María Arroyo-Araujo et al.
Confirmatory multi-lab preclinical trials are a powerful experimental strategy to enable decisions to transition from preclinical to clinical settings. With their complexity, such study designs pose several challenges in statistical plannin...
Blinded-Into-Unblinded Interim Analyses for Clinical Trials With Time-to-Event Endpoints [0.03%]
生存终点临床试验的盲化中间分析与非盲化中间分析
Stephen Schüürhuis,Jan Meis,Björn Bokelmann et al.
Stephen Schüürhuis et al.
A large proportion of clinical trials do not meet their recruitment targets. Trials using time-to-event endpoints come along with the additional complexity that the amount of available information depends on the number of observed events, w...
An Efficient Estimation Method for Longitudinal Data Using Bayesian Conditional Transformation Models [0.03%]
基于贝叶斯条件变换模型的纵向数据高效估计方法
Giovanni Pastori Piccirilli,Márcia D&#x;Elia Branco,Jorge L Bazán
Giovanni Pastori Piccirilli
Bayesian conditional transformation models (BCTMs) address the direct estimation of the conditional distribution function of a random variable Y $Y$ conditional on a set of explanatory variables X ${/rm variables}/ /bm{X}$ . The BCTMs i...
Censoring, Competing Events, and Multistate Models: Comment on Beyersmann et al. "Hazards Constitute Key Quantities for Analyzing, Interpreting and Understanding Time-to-Event Data" [0.03%]
论点：时间事件数据分析、解释和理解的关键在于风险率——评论Beyersmann等人的文章《时间事件数据分析、解释和理解的关键在于风险率》
Malka Gorfine,Daniel Nevo
Malka Gorfine
Beyersmann et al. propose a functional interpretation of hazards, viewing them as evolving quantities describing the entire event process rather than as pointwise causal contrasts. In this commentary, we elaborate on the implications of thi...
Comparison of Different Methods for the Meta-Analysis of Diagnostic Test Accuracy Studies-A Simulation Study [0.03%]
一种评估诊断准确性 meta 分析方法的蒙特卡洛模拟研究
Ferdinand V Stoye,Olaf Raths,Alexander Hapfelmeier et al.
Ferdinand V Stoye et al.
Meta-analysis of diagnostic test accuracy studies aggregates information from multiple studies on sensitivity and specificity. Classical approaches select a single pair of sensitivity and specificity per study (single threshold methods, STM...
Comparative Study
Biometrical journal. Biometrische Zeitschrift. 2026 Aug;68(4):e70147. DOI:10.1002/bimj.70147 2026
Sabine Hoffmann,Simon Lemster,Gary Collins et al.
Sabine Hoffmann et al.
Most original articles published in the medical literature report the results of multiple statistical tests. In a few simple cases, there is agreement on whether to adjust for the number of performed tests. For many cases encountered in pra...
Tina Lang,Frank Konietschke,Jörg Rahnenführer et al.
Tina Lang et al.
Addressing Cluster-Level Treatment Effect Heterogeneity in Sample Size Determination for Hierarchical 2 × 2 Factorial Designs [0.03%]
处理分层2x2析因设计中集群水平治疗异质性对样本量的确定问题
Jiaqi Tong,Fan Li,Guangyu Tong
Jiaqi Tong
A hierarchical 2 × 2 $2/times 2$ factorial design is a type of two-level trial design where the first intervention is randomized at the cluster level and the second intervention is randomized at the individual level. With a continuou...