A comparison of methods for enriching network meta-analyses in the absence of individual patient data [0.03%]
缺乏患者个体数据情况下丰富网络meta分析的比较方法研究
Tanja Proctor,Samuel Zimmermann,Svenja Seide et al.
Tanja Proctor et al.
During drug development, a biomarker is sometimes identified as separating a patient population into those with more and those with less benefit from evaluated treatments. Consequently, later studies might be targeted, while earlier ones ar...
Meta-analysis of dichotomous and ordinal tests with an imperfect gold standard [0.03%]
不完善金标准下的二分类和有序检验的meta分析
Enzo Cerullo,Hayley E Jones,Olivia Carter et al.
Enzo Cerullo et al.
Standard methods for the meta-analysis of medical tests, without assuming a gold standard, are limited to dichotomous data. Multivariate probit models are used to analyse correlated dichotomous data, and can be extended to model ordinal dat...
Meta-Analysis
Research synthesis methods. 2022 Sep;13(5):595-611. DOI:10.1002/jrsm.1567 2022
Clara Domínguez Islas,Kenneth M Rice
Clara Domínguez Islas
Bayesian methods seem a natural choice for combining sources of evidence in meta-analyses. However, in practice, their sensitivity to the choice of prior distribution is much less attractive, particularly for parameters describing heterogen...
Parametric G-computation for compatible indirect treatment comparisons with limited individual patient data [0.03%]
参数G-公式化计算与有限的个体患者数据兼容的间接治疗比较
Antonio Remiro-Azócar,Anna Heath,Gianluca Baio
Antonio Remiro-Azócar
Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial differences in effect modifiers and limited patient-level data. MAIC i...
Citationchaser: A tool for transparent and efficient forward and backward citation chasing in systematic searching [0.03%]
追溯引用的工具：高效透明地进行系统检索中的前向和后向引用追踪
Neal R Haddaway,Matthew J Grainger,Charles T Gray
Neal R Haddaway
Systematic searching aims to find all possibly relevant research from multiple sources, the basis for an unbiased and comprehensive evidence base. Along with bibliographic databases, systematic reviewers use a variety of additional methods ...
Wolfgang Viechtbauer,José Antonio López-López
Wolfgang Viechtbauer
Heterogeneity is commonplace in meta-analysis. When heterogeneity is found, researchers often aim to identify predictors that account for at least part of such heterogeneity by using mixed-effects meta-regression models. Another potentially...
Meta-Analysis
Research synthesis methods. 2022 Nov;13(6):697-715. DOI:10.1002/jrsm.1562 2022
Incorporating historical control information in ANCOVA models using the meta-analytic-predictive approach [0.03%]
利用元分析预测方法在ANCOVA模型中引入历史对照信息
Hongchao Qi,Dimitris Rizopoulos,Joost van Rosmalen
Hongchao Qi
The meta-analytic-predictive (MAP) approach is a Bayesian meta-analytic method to synthesize and incorporate information from historical controls in the analysis of a new trial. Classically, only a single parameter, typically the intercept ...
Meta-Analysis
Research synthesis methods. 2022 Nov;13(6):681-696. DOI:10.1002/jrsm.1561 2022
Accuracy of conversion formula for effect sizes: A Monte Carlo simulation [0.03%]
转换效应规模的公式准确性的蒙特卡洛模拟研究
Leo Poom,Anders Af Wåhlberg
Leo Poom
In meta-analysis, effect sizes often need to be converted into a common metric. For this purpose conversion formulas have been constructed; some are exact, others are approximations whose accuracy has not yet been systematically tested. We ...
Crowdsourcing the identification of studies for COVID-19-related Cochrane Rapid Reviews [0.03%]
crowdsourcing新冠肺炎相关加速 Cochrane 系统评价的文献检索工作
Anna Noel-Storr,Gerald Gartlehner,Gordon Dooley et al.
Anna Noel-Storr et al.
Background: Utilisation of crowdsourcing within evidence synthesis has increased over the last decade. Crowdsourcing platform Cochrane Crowd has engaged a global community of 22,000 people from 170 countries. The COVID-19...
On the bias of complete- and shifting-case meta-regressions with missing covariates [0.03%]
关于因缺失混杂变量而产生偏差的完整案例和位移案例的meta回归分析
Jacob M Schauer,Jihyun Lee,Karina Diaz et al.
Jacob M Schauer et al.
Missing covariates is a common issue when fitting meta-regression models. Standard practice for handling missing covariates tends to involve one of two approaches. In a complete-case analysis, effect sizes for which relevant covariates are ...