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<p>This project contains <em>randomised</em> versions of the raw and processed data for PSA001 (social faces), which we are releasing for the <a href="https://psysciacc.org/2019/09/01/introducing-the-psa001-secondary-analysis-challenge/" rel="nofollow">Secondary Analysis Challenge</a>.</p> <p>The primary documentation for how we're releasing these data are in the <a href="https://osf.io/v46q8/" rel="nofollow"><strong>PSA001 Social Faces Data Management Plan.docx</strong></a>, which lives in the top-level of PSA001 project page. Start there for the most complete documentation of this release.</p> <p>The project contains the following files:</p> <ul> <li><code>data_agg_sim.csv</code>: A randomised version of the processed dataset (i.e., with aggregated ratings). The randomised data have a similar structure as the real dataset, but the stimulus and trait labels are randomized to reduce participant identifiability & obscure the exact findings [see PSA1_sim_data.html for details]</li> <li><code>data_agg_sim_codebook.csv</code>: A codebook for the processed dataset</li> <li><code>data_ind_sim.csv</code>: A randomised version of the raw dataset (i.e., pre-aggregation)</li> <li><code>data_ind_sim_codebook.csv</code>: A codebook for the raw dataset</li> <li><code>Karolinska_14trait_judgmentswithlabels.xls</code>: Factor loadings from Oosterhof & Todorov</li> <li><code>Karolinska_ReadMe_Updated2012.txt</code>: Documentation on the factor loadings from Oosterhof & Todorov</li> <li><code>PSA_sim_analysis.html</code>: Documentation of the primary analyses used in this project. Start here if you want to know what analyses the PSA001 project team will be reporting in their Registered Report.</li> <li><code>PSA1_sim_data.html</code>: Documentation of how data_agg_sim.csv was created</li> <li><code>PSA1_sim_data.Rmd</code>: The R file used to generate PSA1_sim_data.html</li> <li><code>regions.csv</code>: A look-up table that translates the region codes used in the raw and processed datasets into the larger regions used for the paper</li> </ul>
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