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Harari, Ofir; Soltanifar, Mohsen; Cappelleri, Joseph C.; Verhoek, Andre; Ouwens, Mario; Daly, Caitlin; Heeg, Bart – Research Synthesis Methods, 2023
Effect modification (EM) may cause bias in network meta-analysis (NMA). Existing population adjustment NMA methods use individual patient data to adjust for EM but disregard available subgroup information from aggregated data in the evidence network. Additionally, these methods often rely on the shared effect modification (SEM) assumption. In this…
Descriptors: Networks, Network Analysis, Meta Analysis, Evaluation Methods
Jackson, Dan; Bowden, Jack; Baker, Rose – Research Synthesis Methods, 2015
Moment-based estimators of the between-study variance are very popular when performing random effects meta-analyses. This type of estimation has many advantages including computational and conceptual simplicity. Furthermore, by using these estimators in large samples, valid meta-analyses can be performed without the assumption that the treatment…
Descriptors: Meta Analysis, Hierarchical Linear Modeling, Computation, Evaluation Methods
Robertson, Clare; Ramsay, Craig; Gurung, Tara; Mowatt, Graham; Pickard, Robert; Sharma, Pawana – Research Synthesis Methods, 2014
We describe our experience of using a modified version of the Cochrane risk of bias (RoB) tool for randomised and non-randomised comparative studies. Objectives: (1) To assess time to complete RoB assessment; (2) To assess inter-rater agreement; and (3) To explore the association between RoB and treatment effect size. Methods: Cochrane risk of…
Descriptors: Risk, Randomized Controlled Trials, Research Design, Comparative Analysis