A causal meta-analysis framework for clinical trials with unequal randomization ratios [0.03%]
不等随机化比例的临床试验因果元分析框架
Dazheng Zhang,Bingyu Zhang,Lu Li et al.
Dazheng Zhang et al.
Meta-analysis synthesizes evidence from multiple randomized clinical trials and informs evidence-based practices across various medical domains. Recently, causally interpretable meta-analysis has been proposed and applied to treatment evalu...
Producing treatment hierarchies in network meta-analysis using probabilistic models and treatment-choice criteria [0.03%]
基于概率模型和治疗选择标准的网状Meta分析中治疗层次结构的构建
Theodoros Evrenoglou,Adriani Nikolakopoulou,Guido Schwarzer et al.
Theodoros Evrenoglou et al.
A key output of network meta-analysis (NMA) is the relative ranking of treatments; nevertheless, it has attracted substantial criticism. Existing ranking methods often lack clear interpretability and fail to adequately account for uncertain...
Marvin Rieck,Anne-Christine Mupepele,Carsten F Dormann
Marvin Rieck
1. Meta-analyses are a reliable method for a quantitative research synthesis. They are, however, prone to specific biases that can be introduced in the process. Such a bias could exist if primary literature produces similar results if comin...
Synthesis challenges in complex evidence: A critical analysis of systematic reviews of face mask efficacy [0.03%]
复杂证据中的合成挑战：面罩效力系统评价的批判性分析
Trisha Greenhalgh,Sahanika Ratnayake,Rebecca Helm et al.
Trisha Greenhalgh et al.
The evaluation of the role of face masks in preventing respiratory infections is a paradigm case in synthesising complex evidence (i.e. extensive, diverse, technically specialised, and with multilevel chains of causality). Primary studies h...
Juyoung Jung,Ariel M Aloe
Juyoung Jung
Bayesian hierarchical models offer a principled framework for adjusting for study-level bias in meta-analysis, but their complexity and sensitivity to prior specifications necessitate a systematic framework for robust application. This stud...
Impact of matrix-construction assumptions on quantitative overlap assessment in overviews: A meta-research study [0.03%]
矩阵构建假设对概览中定量重复性评估的影响：一项元研究
Javier Bracchiglione,Nicolás Meza,Dawid Pieper et al.
Javier Bracchiglione et al.
Overlap of primary studies among multiple systematic reviews (SRs) is a major challenge when conducting overviews. The corrected covered area (CCA) is a metric computed from a matrix of evidence that quantifies overlap. Therefore, the assum...
RaCE: A rank-clustering estimation method for network meta-analysis [0.03%]
一种用于网络meta分析的秩聚类估计方法RaCE
Michael Pearce,Shouhao Zhou
Michael Pearce
Ranking multiple interventions is a crucial task in network meta-analysis (NMA) to guide clinical and policy decisions. However, conventional ranking methods often oversimplify treatment distinctions, potentially yielding misleading conclus...
The application of ROBINS-I guidance in systematic reviews of non-randomised studies: A descriptive study [0.03%]
ROBINS-I在非随机对照研究系统评价中的应用现状描述性研究
Zipporah Iheozor-Ejiofor,Jelena Savović,Russell J Bowater et al.
Zipporah Iheozor-Ejiofor et al.
The ROBINS-I tool is a commonly used tool to assess risk of bias in non-randomised studies of interventions (NRSI) included in systematic reviews. The reporting of ROBINS-I results is important for decision-makers using systematic reviews t...
Guidance for manuscript submissions testing the use of generative AI for systematic review and meta-analysis [0.03%]
关于使用生成式人工智能进行系统评价和Meta分析的手稿投稿指导方针
Oluwaseun Farotimi,Adam Dunn,Caspar J Van Lissa et al.
Oluwaseun Farotimi et al.