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Improving the statistical power of economic experiments using adaptive designs

Author

Listed:
  • Sebastian Jobjörnsson

    (University Medical Center Göttingen)

  • Henning Schaak

    (University of Natural Resources and Life Sciences)

  • Oliver Musshoff

    (Georg-August-Universität Göttingen)

  • Tim Friede

    (University Medical Center Göttingen)

Abstract

An important issue for many economic experiments is how the experimenter can ensure sufficient power in order to reject one or more hypotheses. The paper illustrates how methods for testing multiple hypotheses simultaneously in adaptive, two-stage designs can be used to improve the power of economic experiments. We provide a concise overview of the relevant theory and illustrate the method in three different applications. These include a simulation study of a hypothetical experimental design, as well as illustrations using two data sets from previous experiments. The simulation results highlight the potential for sample size reductions, maintaining the power to reject at least one hypothesis while ensuring strong control of the overall Type I error probability.

Suggested Citation

  • Sebastian Jobjörnsson & Henning Schaak & Oliver Musshoff & Tim Friede, 2023. "Improving the statistical power of economic experiments using adaptive designs," Experimental Economics, Springer;Economic Science Association, vol. 26(2), pages 357-382, April.
    • Handle: RePEc:kap:expeco:v:26:y:2023:i:2:d:10.1007_s10683-022-09773-8
    DOI: 10.1007/s10683-022-09773-8
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    References listed on IDEAS

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    1. Stephen T. Ziliak & Deirdre N. McCloskey, 2004. "Size Matters: The Standard Error of Regressions in the American Economic Review," Econ Journal Watch, Econ Journal Watch, vol. 1(2), pages 331-358, August.
    2. John A. List & Azeem M. Shaikh & Yang Xu, 2019. "Multiple hypothesis testing in experimental economics," Experimental Economics, Springer;Economic Science Association, vol. 22(4), pages 773-793, December.
    3. Nikhil Bhat & Vivek F. Farias & Ciamac C. Moallemi & Deeksha Sinha, 2020. "Near-Optimal A-B Testing," Management Science, INFORMS, vol. 66(10), pages 4477-4495, October.
    4. Walter Lehmacher & Gernot Wassmer, 1999. "Adaptive Sample Size Calculations in Group Sequential Trials," Biometrics, The International Biometric Society, vol. 55(4), pages 1286-1290, December.
    5. John List & Sally Sadoff & Mathis Wagner, 2011. "So you want to run an experiment, now what? Some simple rules of thumb for optimal experimental design," Experimental Economics, Springer;Economic Science Association, vol. 14(4), pages 439-457, November.
    6. Dean Karlan & John A. List, 2007. "Does Price Matter in Charitable Giving? Evidence from a Large-Scale Natural Field Experiment," American Economic Review, American Economic Association, vol. 97(5), pages 1774-1793, December.
    7. Charles Bellemare & Luc Bissonnette & Sabine Kröger, 2016. "Simulating power of economic experiments: the powerBBK package," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 2(2), pages 157-168, November.
    8. Brennan S Thompson & Matthew D Webb, 2019. "A simple, graphical approach to comparing multiple treatments," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 188-205.
    9. De Long, J Bradford & Lang, Kevin, 1992. "Are All Economic Hypotheses False?," Journal of Political Economy, University of Chicago Press, vol. 100(6), pages 1257-1272, December.
    10. Oliver Musshoff & Norbert Hirschauer, 2014. "Using business simulation games in regulatory impact analysis - the case of policies aimed at reducing nitrogen leaching," Applied Economics, Taylor & Francis Journals, vol. 46(25), pages 3049-3060, September.
    11. John P. A. Ioannidis & T. D. Stanley & Hristos Doucouliagos, 2017. "The Power of Bias in Economics Research," Economic Journal, Royal Economic Society, vol. 127(605), pages 236-265, October.
    12. Maximilian Kasy & Anja Sautmann, 2021. "Adaptive Treatment Assignment in Experiments for Policy Choice," Econometrica, Econometric Society, vol. 89(1), pages 113-132, January.
    13. Eszter Czibor & David Jimenez‐Gomez & John A. List, 2019. "The Dozen Things Experimental Economists Should Do (More of)," Southern Economic Journal, John Wiley & Sons, vol. 86(2), pages 371-432, October.
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    More about this item

    Keywords

    Adaptive design; Multiple testing; Simulation study; Family-wise error rate; Experimental design;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General

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