network-meta-analysis

Network meta-analysis compares multiple treatments simultaneously by combining direct and indirect evidence from study data to generate treatment comparisons, network plots, and league tables.

Indirect comparisons in network meta-analysis estimate treatment effects between interventions without head-to-head trials by leveraging direct evidence across a connected network of studies.

Assessing transitivity and consistency in an NMA model involves evaluating whether direct and indirect evidence align across the network, using frequentist or Bayesian modeling approaches.

Treatment ranking in network meta-analysis is supported using frequentist netmeta and Bayesian BUGSnet approaches to calculate ranking metrics like SUCRA and P-scores.

Generating a league table and network plot requires inputting prepared clinical trial data into the NMA model to visualize treatment networks and summarize comparison outcomes.

Network meta-analysis is needed when comparing multiple interventions simultaneously beyond standard pairwise meta-analysis, synthesizing both direct and indirect evidence to inform clinical decisions.