PLoS ONE · 2013 · 2.4K citations · 42 references
Public HealthBiostatisticsEpidemiologic MethodsMeta-analysisStatisticsCausal Graphical ModelsNetwork Meta-analysisModel Assumptions AssessmentMulti-outcome Network Meta-analysis
Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results.
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Bias in meta-analysis detected by a simple, graphical test
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