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Teaching Integrity in Empirical Research: A Protocol for Documenting Data Management and Analysis

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  • Richard Ball
  • Norm Medeiros

Abstract

This article describes a protocol the authors developed for teaching undergraduates to document their statistical analyses for empirical research projects so that their results are completely reproducible and verifiable. The protocol is guided by the principle that the documentation prepared to accompany an empirical research project should be sufficient to allow an independent researcher to replicate easily and exactly every step of the data management and analysis that generated the results reported in a study. The authors hope that requiring students to follow this protocol will not only teach them how to document their research appropriately, but also instill in them the belief that such documentation is an important professional responsibility.

Suggested Citation

  • Richard Ball & Norm Medeiros, 2012. "Teaching Integrity in Empirical Research: A Protocol for Documenting Data Management and Analysis," The Journal of Economic Education, Taylor & Francis Journals, vol. 43(2), pages 182-189, April.
    • Handle: RePEc:taf:jeduce:v:43:y:2012:i:2:p:182-189
    DOI: 10.1080/00220485.2012.659647
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    References listed on IDEAS

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    1. J. Scott Long, 2009. "The Workflow of Data Analysis Using Stata," Stata Press books, StataCorp LP, number wdaus, March.
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    Cited by:

    1. Hernández Alemán, Anastasia & León, Carmelo J., 2018. "La Réplica en el Análisis Económico Aplicado/Replication in Applied Economic Analysis," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 36, pages 317-332, Enero.
    2. Knittel Christopher R. & Metaxoglou Konstantinos, 2018. "Working with Data: Two Empiricists’ Experience," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-12, January.
    3. Depro, Brooks & Rouse, Kathryn, 2022. "Adapting the case method in an economics capstone research course," International Review of Economics Education, Elsevier, vol. 41(C).
    4. Ben Marwick & Carl Boettiger & Lincoln Mullen, 2018. "Packaging Data Analytical Work Reproducibly Using R (and Friends)," The American Statistician, Taylor & Francis Journals, vol. 72(1), pages 80-88, January.

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