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Publication Year: 2019

1 to 10 of 11,890 Results

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...
Prediction-of-Depression-Main-and-Supplemental-Analyses.pdf Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions Adobe PDF - 416.4 KB - MD5: 116094dc013b24606e93fd4a354104c8
Prediction of Depression - Main and Supplemental Analyses_ Version 2 _01252021.Rmd Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions Unknown - 32.7 KB - MD5: ca2e272414c9ec824384e1c6a26b89d6
pre_imputed_data.RData Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions R Data - 108.7 KB - MD5: e190783ecc2296394b58fae0787ffb04
r56_complete_data.RData Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions R Data - 271.5 KB - MD5: 1cd351f8a92d1530ecfc5cf0f6adedfc
R56_for_ML_act.RData Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions R Data - 114.4 KB - MD5: c912af89b65e62b24984a309b013d3be
R56_for_ML.RData Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions R Data - 114.2 KB - MD5: e7607f3aebc87073e53b7e24e74e146a
R56_imputed_act.RData Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions R Data - 113.1 KB - MD5: 0e47d77d35f8016840e56f29492ffdb6
Instances for Computational Study on New Multi-echelon Supply Chain Network Design Feb 9, 2021 - Haibo Wang Dataverse Wang, Haibo, 2019, "Instances for Computational Study on New Multi-echelon Supply Chain Network Design", https://doi.org/10.18738/T8/PPZN3Q, Texas Data Repository, V11 two dimensional matrix for fcx, fcy and qxy input data files and the problem size from 210 by 72 to 71,721 by 90,720 The data format for p5k6w7s9d8-fcx-1.txt: number-of-rows(30) number-of-columns(7) fcx fcx fcx ...fcx ..... The data format for p5k6w7s9d8-qxy-1.txt: number-of-rows...
p48k42w45s1839d39-qxy-2.txt.gz_aa Feb 9, 2021 - Instances for Computational Study on New Multi-echelon Supply Chain Network Design Gzip Archive - 1.0 GB - MD5: a2ce22769f402746b3f857b6015103e8

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...

Prediction-of-Depression-Main-and-Supplemental-Analyses.pdf

Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions

Adobe PDF - 416.4 KB - MD5: 116094dc013b24606e93fd4a354104c8

Prediction of Depression - Main and Supplemental Analyses_ Version 2 _01252021.Rmd

Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions

Unknown - 32.7 KB - MD5: ca2e272414c9ec824384e1c6a26b89d6

pre_imputed_data.RData

Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions

R Data - 108.7 KB - MD5: e190783ecc2296394b58fae0787ffb04

r56_complete_data.RData

Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions

R Data - 271.5 KB - MD5: 1cd351f8a92d1530ecfc5cf0f6adedfc

R56_for_ML_act.RData

Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions

R Data - 114.4 KB - MD5: c912af89b65e62b24984a309b013d3be

R56_for_ML.RData

Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions

R Data - 114.2 KB - MD5: e7607f3aebc87073e53b7e24e74e146a

R56_imputed_act.RData

Feb 11, 2021 - Replication Data for: Multifactorial Prediction of Depression Diagnosis and Symptom Dimensions

R Data - 113.1 KB - MD5: 0e47d77d35f8016840e56f29492ffdb6

Instances for Computational Study on New Multi-echelon Supply Chain Network Design

Feb 9, 2021 - Haibo Wang Dataverse

Wang, Haibo, 2019, "Instances for Computational Study on New Multi-echelon Supply Chain Network Design", https://doi.org/10.18738/T8/PPZN3Q, Texas Data Repository, V11

two dimensional matrix for fcx, fcy and qxy input data files and the problem size from 210 by 72 to 71,721 by 90,720 The data format for p5k6w7s9d8-fcx-1.txt: number-of-rows(30) number-of-columns(7) fcx fcx fcx ...fcx ..... The data format for p5k6w7s9d8-qxy-1.txt: number-of-rows...

p48k42w45s1839d39-qxy-2.txt.gz_aa

Feb 9, 2021 - Instances for Computational Study on New Multi-echelon Supply Chain Network Design

Gzip Archive - 1.0 GB - MD5: a2ce22769f402746b3f857b6015103e8

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