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Clustering Standard Errors at the "Session" Level

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  • Duk Gyoo Kim

Abstract

Session-specific features of a laboratory experiment, if those exist, do not disappear by clustering standard errors at the session level. Randomly ordering sessions, which is crucial to deal with sampling issues, cannot justify clustering the standard errors at the session level. The experimental design should primarily determine the clustering level. In a typical controlled laboratory experiment where subjects make choices in the same environment repeatedly, clustering at a participant level is inherited from the experimental design, and standard errors could be larger (that is, statistical inference can be more conservative) when clustered at the individual or decision-group level than the session level. It implies that clustering standard errors at the session level can lead to false-positive treatment effects if it is mistakenly chosen. A rule of thumb using standard deviations is introduced.

Suggested Citation

  • Duk Gyoo Kim, 2020. "Clustering Standard Errors at the "Session" Level," CESifo Working Paper Series 8386, CESifo.
  • Handle: RePEc:ces:ceswps:_8386
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    File URL: https://www.cesifo.org/DocDL/cesifo1_wp8386.pdf
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    References listed on IDEAS

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    Cited by:

    1. Igor Asanov & Christoph Buehren & Panagiota Zacharodimou, 2020. "The power of experiments: How big is your n?," MAGKS Papers on Economics 202032, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

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    More about this item

    Keywords

    lab experiment; cluster-adjusted standard errors;

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General

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