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<h1>Project outline for 2011_9</h1> <p><strong>Keywords:</strong> EEG; ERP; scalar implicature</p> <p><strong>Overview:</strong> Exp. 2 from Hartshorne, Snedeker, et al., 2015. An ERP investigation of scalar implicature. See paper for details.</p> <p>This repository contains some of the analysis scripts. The full dataset can be found <a href="https://bitbucket.org/l3atbc/2011_9" rel="nofollow">here</a>.</p> <hr> <p><strong>Publications:</strong> </p> <ol> <li> <p>Hartshorne, Joshua K., Jesse Snedeker, Stephanie Yun-Mun Liem Azar, and Albert Kim. (2015). The neural computation of scalar implicature. Language, Cognition, & Neuroscience, 30(5), 620-634. <a href="http://www.tandfonline.com/doi/abs/10.1080/23273798.2014.981195" rel="nofollow">link</a> Experiment 2</p> </li> <li> <p>Hartshorne, Joshua K., Jesse Snedeker & Albert Kim. (2012). The neural computation of scalar implicature. Architectures and Mechanisms in Language Processing (AMLaP), Riva del Garda, Italy.</p> </li> </ol> <p><strong>Team:</strong></p> <ol> <li>Joshua Hartshorne</li> <li>Al Kim</li> <li>Jesse Snedeker</li> <li>A whole bunch of KimLab RAs</li> </ol> <p><strong>Data Collection:</strong></p> <p>Boulder, 2011</p> <p><strong>Notes:</strong></p> <p>Primary analysis scripts are in clusteranalysis_t.R, which does the cluster analyses described in the paper. (clusternalaysis.R is an older verison based on a different statistic -- ANOVAs, I think.). ClusterPlotting.R should help create the visuals of cluster analyses shown in the paper.</p> <p>The preprocessing was conducted using (I think) Neuroscan software. The relevant processing files appear to be in the folder ProcessingScripts.</p> <p>Note that the permutation analyses used permute (separately) both the within-subjects and between-subjects factors. This is somewhat controversial, in that permutation theory does not justify this analysis, but simulations suggest it is unproblematic (we are working on a paper covering this issue). In this particular case, permuting only the within-subjects factor would probably have been preferred. Based on the size of the effect, however, this is unlikely to matter.</p>
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