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Replication and preregistration

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  • Merton S. Krause

Abstract

Replicability of an experiment’s results is necessary for relying on its results but is extremely difficult to achieve. The difficulty is that besides having the same valid measure across the intended replicates for each dimension and the same comprehensive case population sample coverage, each replicate must have the same fully sufficient set of causally relevant input and effect relevant outcome dimensions. Otherwise the un-included necessary input and outcome dimensions may be at different levels across the intended replicates. Case sample or dimension measure differences across intended replicates can have similar consequences. To ensure all the necessary comparability and so accurate replication of an experiment preregistration and precise oversight of its intended replicates are necessary for every attempt to replicate an experiment in order to promote complete conformity to all the necessary features of its design.

Suggested Citation

  • Merton S. Krause, 2019. "Replication and preregistration," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2647-2652, September.
    • Handle: RePEc:spr:qualqt:v:53:y:2019:i:5:d:10.1007_s11135-019-00877-7
    DOI: 10.1007/s11135-019-00877-7
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    References listed on IDEAS

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    1. George Peat & Richard D Riley & Peter Croft & Katherine I Morley & Panayiotis A Kyzas & Karel G M Moons & Pablo Perel & Ewout W Steyerberg & Sara Schroter & Douglas G Altman & Harry Hemingway & for th, 2014. "Improving the Transparency of Prognosis Research: The Role of Reporting, Data Sharing, Registration, and Protocols," PLOS Medicine, Public Library of Science, vol. 11(7), pages 1-8, July.
    2. Merton Krause, 2013. "The incompatibility of achieving a fully specified linear model with assuming that residual dependent-variable variance is random," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(6), pages 3201-3204, October.
    3. Richard McElreath & Paul E Smaldino, 2015. "Replication, Communication, and the Population Dynamics of Scientific Discovery," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-16, August.
    4. Marcus R. Munafò & Brian A. Nosek & Dorothy V. M. Bishop & Katherine S. Button & Christopher D. Chambers & Nathalie Percie du Sert & Uri Simonsohn & Eric-Jan Wagenmakers & Jennifer J. Ware & John P. A, 2017. "A manifesto for reproducible science," Nature Human Behaviour, Nature, vol. 1(1), pages 1-9, January.
    5. Nosek, Brian A. & Ebersole, Charles R. & DeHaven, Alexander Carl & Mellor, David Thomas, 2018. "The Preregistration Revolution," OSF Preprints 2dxu5, Center for Open Science.
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