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pedlr-main-data
geforkt von koch_means_cook/pedlr-main-data
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10.12751/g-node.9gm3lt
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Source data for the pedlr project by Christoph Koch, Ondrej Zika, Rasmus Bruckner, and Nicolas W. Schuck. Details in DataCite file.

Associated GitHub repository with analysis code: DOI: 10.5281/zenodo.10211239 or https://github.com/koch-means-cook/pedlr/tree/master

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README.md

pedlr-main-data

Source data for the pedlr project by Christoph Koch, Ondrej Zika, Rasmus Bruckner, and Nicolas W. Schuck. This data contains anonymized data of participants solving a decision making task specified in Koch, C., Zika, O., Bruckner, R., & Schuck, N. W. Influence of surprise on reinforcement learning in younger and older adults. (https://doi.org/10.31234/osf.io/unx5y).

The task and all analysis code are included in the associated GitHub repository with analysis code: https://doi.org/10.5281/zenodo.10211239. Using the analysis code on this source data creates an derivative dataset available at https://doi.org/10.12751/g-node.tsq6sg that includes all results reported in Koch, C., Zika, O., Bruckner, R., & Schuck, N. W. Influence of surprise on reinforcement learning in younger and older adults. (https://doi.org/10.31234/osf.io/unx5y).

For a description of the repositories structure see a commented folder structure below.

Datalad

This is a datalad repository. For more information on how to use and set up datalad on your machine please see https://www.datalad.org/.

A thorough walkthrough on how to use datalad is given by the datalad handbook. See the installation page in the datalad handbook for more information about setup and configuration of datalad.

Usage

Once you have datalad installed on your machine you can clone the dataset (e.g. via https) using

datalad clone https://gin.g-node.org/koch_means_cook/pedlr-main-data.git

For in integrated usage with the analysis described in the referenced preprint (Koch, C., Zika, O., Bruckner, R., & Schuck, N. W. Influence of surprise on reinforcement learning in younger and older adults. https://doi.org/10.31234/osf.io/unx5y) clone the Github code repository (doi:10.5281/zenodo.10211239), then clone this datalad repository into the code repository and rename the datalad repository folder to data. This will allow the analysis scripts to directly use this dataset.

Large files will not be downloaded automatically. To get them, you can use

datalad get <filename>

Large files that have been downloaded will be 'locked' and therefore read-only. If you wish to write you will need to unlock them using

datalad unlock <filename>

For more information on locked/unlocked files see here.

Content

├── exclusions.tsv         # List of excluded participants
├── LICENSE                # License file (CC-BY-SA 4.0)
├── README.md              # This file
├── 09RI1ZH_exp_data.tsv   # Example file: tab-separated file of participants behavior
└── (...)

License

This data set is published under a CC-BY-SA 4.0 license.

datacite.yml
Title Pedlr Data
Authors Koch,Christoph;Universität Hamburg, Hamburg, Germany;ORCID:0000-0002-4620-9577
Zika,Ondrej;Max Plank Institute for Human Development, Berlin, Germany;ORCID:0000-0003-0483-4443
Bruckner,Rasmus;Freie Universität Berlin, Berlin, Germany;ORCID:0000-0002-3033-6299
Schuck,Nicolas W.;Universität Hamburg, Hamburg, Germany;ORCID:0000-0002-0150-8776
Description This is the source data set of of the Pedlr project. This contains a datalad repository of all behavioral data collected in Prolific. The code repository to this project has the DOI: 10.5281/zenodo.10211239 See the README.md for information about the usage and Datalad.
License Creative Commons Attribution-ShareAlike 4.0 International Public License (https://creativecommons.org/licenses/by-sa/4.0/deed.en)
References Koch C, Zika O, Bruckner R, Schuck NW (2023) Influence of surprise on reinforcement learning in younger and older adults. https://doi.org/10.31234/osf.io/unx5y [doi:10.31234/osf.io/unx5y] (IsSupplementTo)
Koch C, Zika O, Bruckner R, Schuck NW (2023) Pedlr derivatives. G-Node. https://doi.org/10.12751/g-node.tsq6sg [doi:10.12751/g-node.tsq6sg] (IsReferencedBy)
Koch C, Zika O, Bruckner R, Schuck NW (2023), Pedlr: Analysis of the dataset. Github. https://doi.org/10.5281/zenodo.10211239 [doi:10.5281/zenodo.10211239] (IsReferencedBy)
Funding MPG, M.TN.A.BILD0004
Keywords Reinforcement Learning
Computational Modeling
Aging
Surprise
Resource Type Dataset