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While most neuroimaging meta-analyses are based on peak coordinate data, the best practice method is an image-based meta-analysis that combines the effect estimates and the standard errors from each study . Various efforts are underway to facilitate sharing of neuroimaging data to make such intensity-based meta-analysis possible (see, e.g. ).
When image data is available for each study, a number of approaches (see  for a review) have been proposed to perform such meta-analysis including combination of standardised statistics, just effect estimates or both effects estimates and their sampling variance. While the latter is the preferred approach in the statistical community , often only standardised estimates are shared, reducing the possible meta-analytic approaches.
In view of the increasing availability of image data for neuroimaging analyses, we introduce IBMA, a toolbox for SPM  providing a set of tools for image-based meta-analysis. The toolbox is freely available at: https://github.com/NeuroimagingMetaAnalysis/ibma.