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1 to 5 of 5 Results
Jul 20, 2020 - Association between negative cognitive bias and depression: A symptom-level approach
Beevers, Christopher, 2019, "Analysis Code and Supplementary Materials for Association between negative cognitive bias and depression: A symptom-level approach", https://doi.org/10.18738/T8/2QPR9Z, Texas Data Repository Dataverse, V2
These files are the supplementary materials and analysis code used to generate the results reported in the Journal of Abnormal manuscript.
Apr 23, 2020 - Efficacy of Attention Bias Modification Training for Depressed Adults: A Randomized Clinical Trial
Beevers, Christopher, 2020, "Pre-print for "Efficacy of Attention Bias Modification Training for Depressed Adults: A Randomized Clinical Trial"", https://doi.org/10.18738/T8/M9ZB1E, Texas Data Repository Dataverse, V1
Pre-prints of "Efficacy of Attention Bias Modification Training for Depressed Adults: A Randomized Clinical Trial."
Mar 18, 2020 - Neurocognitive predictors of self-reported reward responsivity and approach motivation in depression: a data-driven approach
Hsu, Kean; Beevers, Christopher, 2020, "Analysis code and supplemental materials", https://doi.org/10.18738/T8/6ENXZW, Texas Data Repository Dataverse, V1
R markdown files, output, and supplemental tables for manuscript currently under invited resubmission
Jul 1, 2019 - Attention Bias Modification for Major Depressive Disorder: Effects on Attention Bias, Resting State Connectivity, and Symptom Change Dataverse
Beevers, Christopher, 2019, "Data and analysis code for "Attention Bias Modification for Major Depressive Disorder: Effects on Attention Bias, Resting State Connectivity, and Symptom Change"", https://doi.org/10.18738/T8/1JBY2V, Texas Data Repository Dataverse, V1
Raw data and statistical code accompanied by analysis narrative for reproducing pre- and post-ABM means for attention bias and BDI-II from the published paper. We are providing data to help facilitate meta-analyses in the future.
May 25, 2017 - Determining optimal parameters of the Self Referent Encoding Task: A large-scale examination of self-referent cognition and depression Dataverse
Dainer-Best, Justin; Lee, Hae Yeon; Shumake, Jason; Yeager, David; Beevers, Christopher, 2017, "Replication data and code for: Determining optimal parameters of the Self Referent Encoding Task: A large-scale examination of self-referent cognition and depression", https://doi.org/10.18738/T8/XK5PXX, Texas Data Repository Dataverse, V1, UNF:6:q3PMaMwiCbjLrPJXWpd1cg== [fileUNF]
Abstract: Although the Self-Referent Encoding Task (SRET) is commonly used to measure self-referent cognition in depression, many different SRET metrics can be obtained. The current study used best subsets regression with cross-validation and independent test samples to identify...
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