Aggregating data across studies is a central challenge in ensuring cumulative, reproducible science. Meta-analysis is a key statistical tool for this purpose. The goal of this project is to support meta-analysis using MetaLab, an interface and central repository. Our user-friendly, online platform supports collaborative hosting and creation of dynamic meta-analyses, based entirely on open tools. MetaLab implements sustainable curation and update practices, promotes community use for study design, and provides ready-to-use educational material. The platform will lower workload for individual (or groups of) researchers through a crowdsourcing infrastructure, thereby automating and structuring parts of the workflow. MetaLab is supported by a community of researchers and students who can become creators, curators, contributors, and/or users of meta-analyses. Visualization and computation tools allow instant access to meta-analytic results. The analysis pipeline is open and reproducible, enabling external scrutiny. Additionally, an infrastructure for meta-meta-analyses allows MetaLab to address broader conceptual and methodological questions across individual meta-analyses. MetaLab is initially being developed for the case study of early language development, a field in which meta-analytic methods are vastly underused and which will benefit greatly from new meta-analyses created in this project; extensions to other subfields of the social sciences are however easily possible.
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