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Automating network meta‐analysis

Research Synthesis Methods, 2012
Mixed treatment comparison (MTC) (also called network meta‐analysis) is an extension of traditional meta‐analysis to allow the simultaneous pooling of data from clinical trials comparing more than two treatment options. Typically, MTCs are performed using general‐purpose Markov chain Monte Carlo software such as WinBUGS, requiring a model and data to ...
van Valkenhoef, Gert   +5 more
openaire   +4 more sources

Network Meta-analysis

2018
Meta-analyses of randomized controlled trials have been used for several years to combine data from clinical trials and generate estimates of treatment effect associated with a therapeutic intervention in relation to a comparator. In recent years, there has been an added emphasis on comparative effectiveness research since decision makers are often ...
Joseph C. Cappelleri, William L. Baker
openaire   +1 more source

Network Meta-Analysis

2020
Network meta-analysis is a popular way to combine results from several studies (usually randomized trials) comparing several treatments or interventions. It has usually been performed in a Bayesian setting, but recently it has become possible in a frequentist setting using multivariate meta-analysis and meta-regression, implemented in Stata with mvmeta.
Nikolakopoulou, Adriani   +2 more
openaire   +1 more source

Software to Conduct a Meta-Analysis and Network Meta-Analysis

2021
Statistical software for meta-analysis (MA) and network meta-analysis (NMA) have become indispensable for researchers. The aim of this chapter is to introduce key features of MA and NMA software to compare the effectiveness of interventions. Commonly used or routinely maintained statistical software are reviewed, including commercial and open-sourced ...
Caitlin, Daly, Charlene, Soobiah
openaire   +2 more sources

Transportability in Network Meta-analysis

Epidemiology, 2016
Network meta-analysis is an extension of the conventional pair wise meta-analysis to include treatments that have not been compared head to head. It has in recent years caught the interest of clinical investigators in comparative effectiveness research.
Conrad, Kabali, Marya, Ghazipura
openaire   +2 more sources

Individual Patient Data Meta-Analysis and Network Meta-Analysis

2021
Meta-analyses are often conducted using trial-level summary data. However, when individual patient data (IPD ) is available, there is greater flexibility in the analysis and a wider range of statistical models that can be fitted. There are two approaches to fitting IPD models.
openaire   +2 more sources

Multiplicative interaction in network meta‐analysis

Statistics in Medicine, 2014
Meta‐analysis of a set of clinical trials is usually conducted using a linear predictor with additive effects representing treatments and trials. Additivity is a strong assumption. In this paper, we consider models for two or more treatments that involve multiplicative terms for interaction between treatment and trial.
Hans-Peter, Piepho   +2 more
openaire   +2 more sources

Network meta-analysis for diagnostic tests

BMJ Evidence-Based Medicine, 2019
Network meta-analysis (NMA) has enabled the comparison of numerous interventions in the absence of direct head-to-head randomised controlled trials. A new technique describes NMA for diagnostic tests, an approach that can facilitate a similar comparison between different diagnostic tests at different diagnostic thresholds.
openaire   +2 more sources

Network meta-analysis in a nutshell

Evidence Based Mental Health, 2019
In most, if not all, healthcare conditions, there is a plethora of competing interventions with few head-to-head comparisons and classical meta-analysis fails to handle simultaneously the multiple comparisons among interventions. Network meta-analysis is an extension of pairwise meta-analysis to accommodate multiple interventions and comparisons.
openaire   +2 more sources

Deconstructing the Network Meta-analysis

Annals of Emergency Medicine, 2020
Lauren M, Westafer, David L, Schriger
openaire   +2 more sources

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