1 to 10 of 23 Results
Feb 11, 2021 - Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions
McNamara, Molly, 2019, "Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions", https://doi.org/10.18738/T8/DEFPNZ, Texas Data Repository, V2
Data and code for a submitted manuscript. Abstract: While Major Depressive Disorder (MDD) is a leading cause of disability, prior investigations may have been limited by studying single explanatory factors rather than considering multiple etiologies simultaneously. The current st... |
Jul 24, 2020 - SNPs, prediction, and STAR*D trial
Shumake, Jason, 2020, "Data munging code for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D trial"", https://doi.org/10.18738/T8/NVAUFR, Texas Data Repository, V1
Data munging code |
Jul 24, 2020 - SNPs, prediction, and STAR*D trial
Shumake, Jason, 2020, "Primary analysis code and report for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D trial"", https://doi.org/10.18738/T8/YC49CY, Texas Data Repository, V1
Analysis code for the results presented in the manuscript. |
Jul 24, 2020 - SNPs, prediction, and STAR*D trial
Shumake, Jason, 2020, "R scripts for snp selection and ensemble learning for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D", https://doi.org/10.18738/T8/GHJK6C, Texas Data Repository, V1
R scripts for snp selection and ensemble learning in STAR*D trial. |
Jul 24, 2020
Analysis code and supplemental materials for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D trial" |
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, V2
These files are the supplementary materials and analysis code used to generate the results reported in the Journal of Abnormal manuscript. |
Jun 12, 2020 - Efficacy of Attention Bias Modification Training for Depressed Adults: A Randomized Clinical Trial
Shumake, Jason, 2020, "Analysis Reports for "Efficacy of Attention Bias Modification Training for Depressed Adults: A Randomized Clinical Trial"", https://doi.org/10.18738/T8/UWKEFM, Texas Data Repository, V3
Analysis reports for outcome manuscript titled "Efficacy of Attention Bias Modification Training for Depressed Adults: A Randomized Clinical Trial." Reports are RMarkdowns that include the R code and the results from the R code. |
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, V1
Pre-prints of "Efficacy of Attention Bias Modification Training for Depressed Adults: A Randomized Clinical Trial." |
Apr 19, 2020
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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, V1
R markdown files, output, and supplemental tables for manuscript currently under invited resubmission |