In a study using network meta-analysis, the assessment of the influence of the limitations or characteristics of individual studies on the estimates obtained from the network is quite important. The percentage contribution matrix is important in this context as it shows the contribution of each direct treatment effect and its contribution to each treatment effect estimate from network meta-analysis. The peer-reviewed, open access article published in F1000 Research titled "Estimating the contribution of studies in network meta-analysis: paths, flows and streams", funded by one of Campbell's methods grants, makes an important addition to the methodology around network meta-analysis.
One of the co-authors, Georgia Salanti, is the Principal Investigator of the Campbell methods grant for her work with CINeMA (Confidence in Network Meta-Analysis), which is a web application that simplifies the evaluation of confidence in the findings of network meta-analysis. Those who work with analysing indirect evidence and study percentage contributions may find both the article and online tool thought-provoking and useful for their work.
Papakonstantinou T, Nikolakopoulou A, Rücker G et al. Estimating the contribution of studies in network meta-analysis: paths, flows and streams [version 2; referees: 2 approved, 1 approved with reservations]. F1000Research2018, 7:610
CINeMA: Confidence in Network Meta-Analysis [Software]. Institute of Social and Preventive Medicine, University of Bern, 2017. Available from cinema.ispm.ch