Mood Disorders Laboratory Dataverse

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

671 to 680 of 695 Results

srp_and_sret.tab May 21, 2018 - Replication data and materials for Positive Imagery Training Increases Positive Self-Referent Cognition in Depression Tabular Data - 7.6 KB - 22 Variables, 77 Observations - UNF:6:xyNy5AcjCrjA1TcXX19D6w==
Training descriptions.docx May 21, 2018 - Replication data and materials for Positive Imagery Training Increases Positive Self-Referent Cognition in Depression MS Word - 17.7 KB - MD5: 80616e94b0ee2cf80ccc081184a2a196
Replication data and materials for Positive Imagery Training Increases Positive Self-Referent Cognition in Depression(The University of Texas at Austin) May 21, 2018 This dataverse includes replication data and materials for the article entitled "Positive Imagery Training Increases Positive Self-Referent Cognition in Depression".
Replication Data for: Negative self-referential processing is associated with genetic variation in the serotonin transporter-linked polymorphic region (5-HTTLPR): Evidence from two independent studies(University of Texas at Austin) Oct 12, 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 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, 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...
adolescents.tab May 25, 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 Tabular Data - 7.2 KB - 21 Variables, 53 Observations - UNF:6:VU/NihyetA2M0fMiwx/dAw== .Rdata file used for creating models.
adomodel-all.tab May 25, 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 Tabular Data - 6.0 KB - 19 Variables, 53 Observations - UNF:6:PCYcoD4wK+6CiCJl26J+2A== .Rdata file with adolescent best subsets model.
all_fullSRET.tab May 25, 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 Tabular Data - 824.1 KB - 7 Variables, 19230 Observations - UNF:6:kmawaPt21YPL57Xy66cfTg== .Rdata file used for internal reliability analyses.
allthreesamples.tab May 25, 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 Tabular Data - 240.6 KB - 31 Variables, 1309 Observations - UNF:6:BLjx7F+SRVAYe+zIF/dMMw== .Rdata file used for models and summary stats.
correlation tables.Rmd May 25, 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 Unknown - 7.9 KB - MD5: dd3e21dcb2157875b82c87a91b2ac93b R Markdown (.Rmd) file containing code and explanations. Used for creating HTML files at https://jdbest.github.io/sretmodels -- correlates outcome variables for all samples.

srp_and_sret.tab

May 21, 2018 - Replication data and materials for Positive Imagery Training Increases Positive Self-Referent Cognition in Depression

Tabular Data - 7.6 KB - 22 Variables, 77 Observations -

Training descriptions.docx

May 21, 2018 - Replication data and materials for Positive Imagery Training Increases Positive Self-Referent Cognition in Depression

MS Word - 17.7 KB -

Replication data and materials for Positive Imagery Training Increases Positive Self-Referent Cognition in Depression(The University of Texas at Austin)

May 21, 2018

This dataverse includes replication data and materials for the article entitled "Positive Imagery Training Increases Positive Self-Referent Cognition in Depression".

Replication Data for: Negative self-referential processing is associated with genetic variation in the serotonin transporter-linked polymorphic region (5-HTTLPR): Evidence from two independent studies(University of Texas at Austin)

Oct 12, 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

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, 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...

adolescents.tab

May 25, 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

Tabular Data - 7.2 KB - 21 Variables, 53 Observations -

.Rdata file used for creating models.

adomodel-all.tab

May 25, 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

Tabular Data - 6.0 KB - 19 Variables, 53 Observations -

.Rdata file with adolescent best subsets model.

all_fullSRET.tab

May 25, 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

Tabular Data - 824.1 KB - 7 Variables, 19230 Observations -

.Rdata file used for internal reliability analyses.

allthreesamples.tab

May 25, 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

Tabular Data - 240.6 KB - 31 Variables, 1309 Observations -

.Rdata file used for models and summary stats.

correlation tables.Rmd

May 25, 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

Unknown - 7.9 KB -

R Markdown (.Rmd) file containing code and explanations. Used for creating HTML files at https://jdbest.github.io/sretmodels -- correlates outcome variables for all samples.

Add Data

Share Dataverse

Link Dataverse

Reset Modifications