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Equivalence of Entropy Balancing and the Method of Moments for Matching-Adjusted Indirect Comparison
Phillippo, David M.; Dias, Sofia; Ades, A. E.; Welton, Nicky J. – Research Synthesis Methods, 2020
Indirect comparisons are used to obtain estimates of relative effectiveness between two treatments that have not been compared in the same randomized controlled trial, but have instead been compared against a common comparator in separate trials. Standard indirect comparisons use only aggregate data, under the assumption that there are no…
Descriptors: Comparative Analysis, Outcomes of Treatment, Patients, Randomized Controlled Trials
Pedder, Hugo; Boucher, Martin; Dias, Sofia; Bennetts, Margherita; Welton, Nicky J. – Research Synthesis Methods, 2020
Time-course model-based network meta-analysis (MBNMA) has been proposed as a framework to combine treatment comparisons from a network of randomized controlled trials reporting outcomes at multiple time-points. This can explain heterogeneity/inconsistency that arises by pooling studies with different follow-up times and allow inclusion of studies…
Descriptors: Simulation, Randomized Controlled Trials, Meta Analysis, Comparative Analysis
Pedder, Hugo; Dias, Sofia; Bennetts, Margherita; Boucher, Martin; Welton, Nicky J. – Research Synthesis Methods, 2019
Background: Model-based meta-analysis (MBMA) is increasingly used to inform drug-development decisions by synthesising results from multiple studies to estimate treatment, dose-response, and time-course characteristics. Network meta-analysis (NMA) is used in Health Technology Appraisals for simultaneously comparing effects of multiple treatments,…
Descriptors: Meta Analysis, Guidelines, Drug Therapy, Decision Making
Donegan, Sarah; Welton, Nicky J.; Tudur Smith, Catrin; D'Alessandro, Umberto; Dias, Sofia – Research Synthesis Methods, 2017
Background: Many reviews aim to compare numerous treatments and report results stratified by subgroups (eg, by disease severity). In such cases, a network meta-analysis model including treatment by covariate interactions can estimate the relative effects of all treatment pairings for each subgroup of patients. Two key assumptions underlie such…
Descriptors: Network Analysis, Meta Analysis, Outcomes of Treatment, Comparative Analysis