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. 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.
    2. repec:grz:wpsses:2021-02 is not listed on IDEAS
    3. 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.
    4. 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.
    5. repec:grz:wpsses:2021-01 is not listed on IDEAS
    6. Merl, Robert & Palan, Stefan & Schmidt, Dominik & Stöckl, Thomas, 2023. "Insider trading regulation and trader migration," Journal of Financial Markets, Elsevier, vol. 66(C).
    7. repec:hal:journl:hal-04692482 is not listed on IDEAS
    8. 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).

    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. 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).
    2. repec:grz:wpsses:2021-03 is not listed on IDEAS
    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. 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.
    5. 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.
    6. 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).
    7. David J. Cooper & Krista Saral & Marie Claire Villeval, 2021. "Why Join a Team?," Management Science, INFORMS, vol. 67(11), pages 6980-6997, November.
    8. Zakaria Babutsidze & Nobuyuki Hanaki & Adam Zylbersztejn, 2019. "Digital Communication and Swift Trust," SciencePo Working papers Main halshs-02050514, HAL.
    9. 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.
    10. Kamei, Kenju, 2016. "Information Disclosure and Cooperation in a Finitely-repeated Dilemma: Experimental Evidence," MPRA Paper 75100, University Library of Munich, Germany.
    11. Simeon Schudy & Verena Utikal, 2015. "Does imperfect data privacy stop people from collecting personal health data?," TWI Research Paper Series 98, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    12. Sandra Ludwig & Julia Nafziger, 2011. "Beliefs about overconfidence," Theory and Decision, Springer, vol. 70(4), pages 475-500, April.
    13. Xu, Xue & Potters, Jan, 2018. "An experiment on cooperation in ongoing organizations," Journal of Economic Behavior & Organization, Elsevier, vol. 147(C), pages 28-40.
    14. Prokudina, Elena & Renneboog, Luc & Tobler, Philippe, 2015. "Does Confidence Predict Out-of-Domain Effort?," Discussion Paper 2015-055, Tilburg University, Center for Economic Research.
    15. Patricio S Dalton & Victor H Gonzalez Jimenez & Charles N Noussair, 2017. "Exposure to Poverty and Productivity," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-19, January.
    16. Simon Gaechter & Chris Starmer & Fabio Tufano, 2022. "Measuring “group cohesion” to reveal the power of social relationships in team production," Discussion Papers 2022-12, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    17. Friedrich Heinemann & Martin Kocher, 2013. "Tax compliance under tax regime changes," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 20(2), pages 225-246, April.
    18. Amrei Lahno & Marta Serra-Garcia, 2015. "Peer effects in risk taking: Envy or conformity?," Journal of Risk and Uncertainty, Springer, vol. 50(1), pages 73-95, February.
    19. Menusch Khadjavi, 2018. "Deterrence works for criminals," European Journal of Law and Economics, Springer, vol. 46(1), pages 165-178, August.
    20. Bose, Neha & Sgroi, Daniel, 2019. "The Role of Theory of Mind and “Small Talk” Communication in Strategic Decision-Making," CAGE Online Working Paper Series 409, Competitive Advantage in the Global Economy (CAGE).
    21. Leanne Roncolato & Alex Roomets, 2020. "Who will change the “baby?” Examining the power of gender in an experimental setting," Review of Economics of the Household, Springer, vol. 18(3), pages 823-852, September.

    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.