The preregistration revolution
- PMID: 29531091
- PMCID: PMC5856500
- DOI: 10.1073/pnas.1708274114
The preregistration revolution
Abstract
Progress in science relies in part on generating hypotheses with existing observations and testing hypotheses with new observations. This distinction between postdiction and prediction is appreciated conceptually but is not respected in practice. Mistaking generation of postdictions with testing of predictions reduces the credibility of research findings. However, ordinary biases in human reasoning, such as hindsight bias, make it hard to avoid this mistake. An effective solution is to define the research questions and analysis plan before observing the research outcomes-a process called preregistration. Preregistration distinguishes analyses and outcomes that result from predictions from those that result from postdictions. A variety of practical strategies are available to make the best possible use of preregistration in circumstances that fall short of the ideal application, such as when the data are preexisting. Services are now available for preregistration across all disciplines, facilitating a rapid increase in the practice. Widespread adoption of preregistration will increase distinctiveness between hypothesis generation and hypothesis testing and will improve the credibility of research findings.
Keywords: confirmatory analysis; exploratory analysis; methodology; open science; preregistration.
Conflict of interest statement
Conflict of interest statement: B.A.N., A.C.D., and D.T.M. are employed by the nonprofit Center for Open Science that has as its mission to increase openness, integrity, and reproducibility of research.
Comment in
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Reply to Ledgerwood: Predictions without analysis plans are inert.Proc Natl Acad Sci U S A. 2018 Nov 6;115(45):E10518. doi: 10.1073/pnas.1816418115. Epub 2018 Oct 19. Proc Natl Acad Sci U S A. 2018. PMID: 30341224 Free PMC article. No abstract available.
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The preregistration revolution needs to distinguish between predictions and analyses.Proc Natl Acad Sci U S A. 2018 Nov 6;115(45):E10516-E10517. doi: 10.1073/pnas.1812592115. Epub 2018 Oct 19. Proc Natl Acad Sci U S A. 2018. PMID: 30341225 Free PMC article. No abstract available.
References
-
- Box GEP. Science and statistics. J Am Stat Assoc. 1976;71:791–799.
-
- Box GEP. Robustness in the strategy of scientific model building. In: Launer RL, Wilkinson GN, editors. Robustness in Statistics. Academic; New York: 1979. pp. 201–236.
-
- de Groot AD. The meaning of “significance” for different types of research. Acta Psychol (Amst) 2014;148:188–194. - PubMed
-
- Hoyningen-Huene P. Context of discovery and context of justification. Stud Hist Philos Sci. 1987;18:501–515.
-
- Kuhn TS. Logic of discovery or psychology of research? In: Lakatos I, Musgrave A, editors. Criticism and the Growth of Knowledge. Cambridge Univ Press; Cambridge, UK: 1970. pp. 1–23.
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