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arXiv · 2604.16221

Network Meta-analysis and Diffusion

Gerta Rücker·Annabel L. Davies·Guido Schwarzer
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Abstract

We show that the covariance matrix of the treatment effect estimates in a network meta-analysis can be obtained without matrix inversion using a geometric series of diffusion matrices. This property extends to the hat matrix and provides a connection between parameter estimation in regression analysis and random walks on the network graph. We also provide a number of visualization tools implemented in R.

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Gerta Rücker, Annabel L. Davies, Guido Schwarzer. 2026-04-17. Network Meta-analysis and Diffusion. https://arxiv.org/abs/2604.16221

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