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Bayesian belief updating after a replication experiment

  • Alex O. Holcombe (a1) and Samuel J. Gershman (a2)

Abstract

Zwaan et al. and others discuss the importance of the inevitable differences between a replication experiment and the corresponding original experiment. But these discussions are not informed by a principled, quantitative framework for taking differences into account. Bayesian confirmation theory provides such a framework. It will not entirely solve the problem, but it will lead to new insights.

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References

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Duhem, P. (1954) The aim and structure of physical theory. Princeton University Press.
Hawthorne, J. (2014) Bayesian confirmation theory. In: The Bloomsbury Companion to the Philosophy of Science, ed. French, S. & Saatsi, J., p. 197. Bloomsbury Academic.
Rieth, C. A., Piantadosi, S. T., Smith, K. A. & Vul, E. (2013) Put your money where your mouth is: Incentivizing the truth by making nonreplicability costly. European Journal of Personality 27:120–44.
Simons, D. J., Shoda, Y. & Lindsay, D. S. (2017) Constraints on generality (COG): A proposed addition to all empirical papers. Perspectives on Psychological Science 12:1123–28. Available at: http://doi.org/10.1177/1745691617708630.
Strevens, M. (2001) The Bayesian treatment of auxiliary hypotheses. The British Journal for the Philosophy of Science 52(3):515–37.
Strevens, M. (2017) Notes on Bayesian confirmation theory [paper]. Available at: http://www.nyu.edu/classes/strevens/BCT/BCT.pdf.

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