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1 to 10 of 29 Results

Manuscript pre-print Jun 18, 2021 - Prognostic Modeling for Digital Interventions Beevers, Christopher, 2021, "Manuscript pre-print", https://doi.org/10.18738/T8/ZJVQCT, Texas Data Repository, V1 Pre-print of manuscript.
Analysis Reports for manuscript "Change in Negative Attention Bias Mediates the Association Between Attention Bias Modification Training and Depression Symptom Improvement" Jun 18, 2021 - Attention Bias Modification Training - Mediation (R33 grant) Shumake, Jason, 2021, "Analysis Reports for manuscript "Change in Negative Attention Bias Mediates the Association Between Attention Bias Modification Training and Depression Symptom Improvement"", https://doi.org/10.18738/T8/G2KV5B, Texas Data Repository, V1 Analysis reports used for the manuscript "Change in Negative Attention Bias Mediates the Association Between Attention Bias Modification Training and Depression Symptom Improvement"
Attention Bias Modification Training - Mediation (R33 grant)(University of Texas at Austin) Jun 18, 2021 Analysis code for ABMT mediation manuscript
Analysis Code Jun 18, 2021 - Prognostic Modeling for Digital Interventions Jason Shumake, 2021, "Analysis Code", https://doi.org/10.18738/T8/Y9HKXG, Texas Data Repository, V1 Analysis code used to create the simulations presented in the paper.
Simulation Results Tables Jun 18, 2021 - Prognostic Modeling for Digital Interventions Shumake, Jason, 2021, "Simulation Results Tables", https://doi.org/10.18738/T8/ZQLXF3, Texas Data Repository, V1 Data used in simulation figures.
Prognostic Modeling for Digital Interventions(University of Texas at Austin) Jun 18, 2021 Repository for article titled "Not Just ``Big'' Data: Importance of Sample Size, Measurement Error, and Uninformative Predictors for Developing Prognostic Models for Digital Interventions."
Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions 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...
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 STARD trial" Jul 24, 2020 - SNPs, prediction, and STARD 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
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 STARD trial" Jul 24, 2020 - SNPs, prediction, and STARD 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.
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 STARD Jul 24, 2020 - SNPs, prediction, and STARD 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 STARD", https://doi.org/10.18738/T8/GHJK6C, Texas Data Repository, V1 R scripts for snp selection and ensemble learning in STARD trial.

Manuscript pre-print

Jun 18, 2021 - Prognostic Modeling for Digital Interventions

Beevers, Christopher, 2021, "Manuscript pre-print", https://doi.org/10.18738/T8/ZJVQCT, Texas Data Repository, V1

Pre-print of manuscript.

Analysis Reports for manuscript "Change in Negative Attention Bias Mediates the Association Between Attention Bias Modification Training and Depression Symptom Improvement"

Jun 18, 2021 - Attention Bias Modification Training - Mediation (R33 grant)

Shumake, Jason, 2021, "Analysis Reports for manuscript "Change in Negative Attention Bias Mediates the Association Between Attention Bias Modification Training and Depression Symptom Improvement"", https://doi.org/10.18738/T8/G2KV5B, Texas Data Repository, V1

Analysis reports used for the manuscript "Change in Negative Attention Bias Mediates the Association Between Attention Bias Modification Training and Depression Symptom Improvement"

Attention Bias Modification Training - Mediation (R33 grant)(University of Texas at Austin)

Jun 18, 2021

Analysis code for ABMT mediation manuscript

Analysis Code

Jun 18, 2021 - Prognostic Modeling for Digital Interventions

Jason Shumake, 2021, "Analysis Code", https://doi.org/10.18738/T8/Y9HKXG, Texas Data Repository, V1

Analysis code used to create the simulations presented in the paper.

Simulation Results Tables

Jun 18, 2021 - Prognostic Modeling for Digital Interventions

Shumake, Jason, 2021, "Simulation Results Tables", https://doi.org/10.18738/T8/ZQLXF3, Texas Data Repository, V1

Data used in simulation figures.

Prognostic Modeling for Digital Interventions(University of Texas at Austin)

Jun 18, 2021

Repository for article titled "Not Just ``Big'' Data: Importance of Sample Size, Measurement Error, and Uninformative Predictors for Developing Prognostic Models for Digital Interventions."

Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions

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...

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"

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

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"

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.

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

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.

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