IDEAS home Printed from https://ideas.repec.org/a/eee/beexfi/v22y2019icp1-2.html
   My bibliography  Save this article

Importing z-Tree data into R

Author

Listed:
  • Kirchkamp, Oliver

Abstract

The software z-Tree is used for thousands of economic experiments worldwide. z-Tree stores experimental data in a way that minimizes the risk of losing data. However, it may be cumbersome to manually read this data into a statistical package. The purpose of the R-package zTree is to make the process of importing data from z-Tree into the statistical package R transparent, reproducible and simple.

Suggested Citation

  • Kirchkamp, Oliver, 2019. "Importing z-Tree data into R," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 1-2.
    • Handle: RePEc:eee:beexfi:v:22:y:2019:i:c:p:1-2
    DOI: 10.1016/j.jbef.2018.11.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2214635018302569
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jbef.2018.11.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Roger Koenker & Achim Zeileis, 2009. "On reproducible econometric research," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 833-847.
    2. Wickham, Hadley, 2011. "The Split-Apply-Combine Strategy for Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i01).
    3. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mitterbacher, Kerstin & Fleiß, Jürgen & Palan, Stefan, 2024. "Reciprocity in migration policy and labor market integration: A lab experiment," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 1-16.
    2. repec:grz:wpsses:2021-01 is not listed on IDEAS
    3. Merl, Robert & Palan, Stefan & Schmidt, Dominik & Stöckl, Thomas, 2023. "Insider trading regulation and trader migration," Journal of Financial Markets, Elsevier, vol. 66(C).
    4. Kan Takeuchi, 2023. "ztree2stata: a data converter for z-Tree and Stata users," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 9(1), pages 136-146, June.
    5. Dominik Schmidt & Thomas Stöckl & Stefan Palan, 2024. "Voting for insider trading regulation. An experimental study of informed and uninformed traders’ preferences," Post-Print hal-04692482, HAL.
    6. repec:grz:wpsses:2021-02 is not listed on IDEAS
    7. Fidanoski, Filip & Johnson, Timothy, 2023. "A z-Tree implementation of the Dynamic Experiments for Estimating Preferences [DEEP] method," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    8. Luciano Andreozzi & Matteo Ploner & Ali Seyhun Saral, 2019. "The Stability of Conditional Cooperation: Egoism Trumps Reciprocity in Social Dilemmas," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2019_12, Max Planck Institute for Research on Collective Goods.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:grz:wpsses:2021-03 is not listed on IDEAS
    2. Merl, Robert & Stöckl, Thomas & Palan, Stefan, 2023. "Insider trading regulation and shorting constraints. Evaluating the joint effects of two market interventions," Journal of Banking & Finance, Elsevier, vol. 154(C).
    3. Klijn, Flip & Pais, Joana & Vorsatz, Marc, 2019. "Static versus dynamic deferred acceptance in school choice: Theory and experiment," Games and Economic Behavior, Elsevier, vol. 113(C), pages 147-163.
    4. Ederer, Florian & Stremitzer, Alexander, 2017. "Promises and expectations," Games and Economic Behavior, Elsevier, vol. 106(C), pages 161-178.
    5. Bosch-Domènech, Antoni & Vriend, Nicolaas J., 2013. "On the role of non-equilibrium focal points as coordination devices," Journal of Economic Behavior & Organization, Elsevier, vol. 94(C), pages 52-67.
    6. Eva M. Krockow & Masanori Takezawa & Briony D. Pulford & Andrew M. Colman & Samuel Smithers & Toshimasa Kita & Yo Nakawake, 2018. "Commitment-enhancing tools in Centipede games: Evidencing European–Japanese differences in trust and cooperation," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(1), pages 61-72, January.
    7. Wendelin Schnedler & Nina Lucia Stephan, 2020. "Revisiting a Remedy Against Chains of Unkindness," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(3), pages 347-364, July.
    8. Kyung Hwan Baik & Subhasish M. Chowdhury & Abhijit Ramalingam, 2021. "Group size and matching protocol in contests," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(4), pages 1716-1736, November.
    9. Radu Vranceanu & Damien Besancenot & Delphine Dubart, 2014. "Can Rumors and Other Uninformative Messages Cause Illiquidity ?," CEPN Working Papers hal-00841167, HAL.
    10. Basteck, Christian & Klaus, Bettina & Kübler, Dorothea, 2021. "How lotteries in school choice help to level the playing field," Games and Economic Behavior, Elsevier, vol. 129(C), pages 198-237.
    11. Ertac, Seda & Gumren, Mert & Gurdal, Mehmet Y., 2020. "Demand for decision autonomy and the desire to avoid responsibility in risky environments: Experimental evidence," Journal of Economic Psychology, Elsevier, vol. 77(C).
    12. David J. Cooper & Krista Saral & Marie Claire Villeval, 2021. "Why Join a Team?," Management Science, INFORMS, vol. 67(11), pages 6980-6997, November.
    13. Robert Gazzale & Julian Jamison & Alexander Karlan & Dean Karlan, 2013. "Ambiguous Solicitation: Ambiguous Prescription," Economic Inquiry, Western Economic Association International, vol. 51(1), pages 1002-1011, January.
    14. Zakaria Babutsidze & Nobuyuki Hanaki & Adam Zylbersztejn, 2019. "Digital Communication and Swift Trust," SciencePo Working papers Main halshs-02050514, HAL.
    15. Morone, A. & Morone, P. & Germani, A.R., 2014. "Individual and group behaviour in the traveler's dilemma: An experimental study," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 49(C), pages 1-7.
    16. Falk Armin & Kosfeld Michael, 2012. "It's all about Connections: Evidence on Network Formation," Review of Network Economics, De Gruyter, vol. 11(3), pages 1-36, September.
    17. Wojciech Hardy & Michal Krawczyk & Joanna Tyrowicz, 2015. ""Thou shalt not leech" Are digital pirates conditional cooperators?," Working Papers 2015-26, Faculty of Economic Sciences, University of Warsaw.
    18. Galliera, Arianna, 2018. "Self-selecting random or cumulative pay? A bargaining experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 72(C), pages 106-120.
    19. Kamei, Kenju, 2016. "Information Disclosure and Cooperation in a Finitely-repeated Dilemma: Experimental Evidence," MPRA Paper 75100, University Library of Munich, Germany.
    20. Delaney, Jason & Jacobson, Sarah, 2014. "Those outsiders: How downstream externalities affect public good provision," Journal of Environmental Economics and Management, Elsevier, vol. 67(3), pages 340-352.
    21. Breaban, Adriana & van de Kuilen, Gijs & Noussair, Charles, 2016. "Prudence, Personality, Cognitive Ability and Emotional State," Other publications TiSEM 9a01a5ab-e03d-49eb-9cd7-4, Tilburg University, School of Economics and Management.

    More about this item

    Keywords

    z-Tree; Reproducible research;

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:beexfi:v:22:y:2019:i:c:p:1-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-behavioral-and-experimental-finance .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.