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<p>This project attempts to conduct a crowdsourced data analysis <a href="https://journals.sagepub.com/doi/full/10.1177/2515245917747646" rel="nofollow">(Silberzahn et al., 2018)</a> of an anonymised dataset to determine the extent to which statistical results depends on the way in which they are computed. It has two phases. </p> <p><strong>Phase 1: crowdsourced data analysis</strong></p> <p>Each participating teams will analyse a dataset synthesised from the <a href="http://www.bristol.ac.uk/alspac/" rel="nofollow">Avon Longitudinal Study of Parents and Children (ALSPAC)</a> and submit their analyses to the project coordinators: Katie Drax and Robert Arbon. The analyses will be re-run on the original ALSPAC data individually and as part of a multiverse analysis <a href="https://journals.sagepub.com/doi/full/10.1177/1745691616658637?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dpubmed" rel="nofollow">(Steegen et al., 2016)</a>. The results of the individual analyses and the multiverse analysis on the ALSPAC data will be returned to the teams. </p> <p>Teams were asked to submit their analyses by 24 June, 2019. All participants who contribute to phase 1 will earn authorship on any resulting publication.</p> <p><strong>Phase 2: Data Visualisation Challenge</strong></p> <p>The results from phase 1 will be released soon. Anyone interested in data visualisation is invited to attempt to visualise the results and submit their attempts to the project coordinators. The visualisations will be judged and a prize of £500 and a trophy awarded to the team with the best one.</p> <p>If you have any questions please email the project coordinators at maps-project@bristol.ac.uk.</p>
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