The Preregistration Revolution
Year: 2017
Type: preprint
Abstract: Progress in science relies 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 prior to observing the research outcomes--a process called preregistration. 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 pre-existing. 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.
Institutions: Center for Open Science, University of Virginia
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4239513977