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Inductive Inference and Replications: A Bayesian Perspective

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  • Raman, Kalyan

Abstract

A probabilistic model is proposed to assess the value of replications. The corroboration of a theory is shown to be a function of the number of replications, the number of successful outcomes, and our initial beliefs. An adaptive control model provides the optimal policy for continuing replications, given the accumulated evidence for the theory, the precision deemed necessary, and the cost of replicating. Copyright 1994 by the University of Chicago.

Suggested Citation

  • Raman, Kalyan, 1994. "Inductive Inference and Replications: A Bayesian Perspective," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(4), pages 633-643, March.
    • Handle: RePEc:oup:jconrs:v:20:y:1994:i:4:p:633-43
    DOI: 10.1086/209375
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    Cited by:

    1. Peterson, Robert A. & Merunka, Dwight R., 2014. "Convenience samples of college students and research reproducibility," Journal of Business Research, Elsevier, vol. 67(5), pages 1035-1041.
    2. Pierre Berthon & Leyland Pitt & Michael Ewing & Christopher L. Carr, 2002. "Potential Research Space in MIS: A Framework for Envisioning and Evaluating Research Replication, Extension, and Generation," Information Systems Research, INFORMS, vol. 13(4), pages 416-427, December.
    3. Robert A. Peterson & U. N. Umesh, 2018. "On the significance of statistically insignificant results in consumer behavior experiments," Journal of the Academy of Marketing Science, Springer, vol. 46(1), pages 81-91, January.
    4. Hubbard, Raymond & Vetter, Daniel E., 1996. "An empirical comparison of published replication research in accounting, economics, finance, management, and marketing," Journal of Business Research, Elsevier, vol. 35(2), pages 153-164, February.

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