Using variable selection methods in network meta-analysis
Abstract
The current thesis aims to address two common challenges encountered in network meta-analysis (NMA), the evaluation of consistency and the handling of multi-component interventions. Consistency assessment is vital as the validity of the NMA findings is primary affected by the satisfaction of this assumption. Significant discrepancies between direct and indirect evidence may lead to biased NMA estimates. In particular, a brief overview of (N)MA and the standard method used to evaluate consistency is presented. Additionally, a novel method for identifying inconsistencies is proposed that evaluates network consistency both globally and locally. This was accomplished by integrating the Stochastic Search Variable Selection method into the NMA framework and treating inconsistency factors as variables in a generalized linear model. Historical evidence and differences between direct and indirect evidence that are considered of practical significant, can be also incorporated into the inconsiste ...
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