Preregistration
Preregistration involves publicly recording your research hypotheses, study design, and analysis plans before data collection begins. Far from reducing the space for creativity and discovery, preregistration helps researchers to think systematically about the theoretical framing of the empirical steps improves creativity and widens opportunities for discovery. This practice strengthens transparency and accountability by reducing questionable research practices such as p-hacking, data dredging, and selective reporting.
Researchers typically can preregister their studies by uploading a protocol to a trusted platform such as the Open Science Framework (OSF) or AsPredicted. The protocol is timestamped and can be made public immediately or kept under embargo until publication.
By specifying hypotheses, variables, and planned analyses in advance, preregistration distinguishes confirmatory analyses from exploratory work, enhancing the credibility, reproducibility, and integrity of quantitative research.
Preregistration is not about imprisoning research. While promoting transparency, it also allows researchers to deviate from their original plans so long as any changes are documented and explained transparently.
As part of open research practices, preregistration is increasingly encouraged or required by journals, funding agencies, and the Research Excellence Framework (REF), reinforcing its role in producing robust and trustworthy findings.
No Action (Quant.)
Studies are not preregistered, and research hypotheses, methods, or analysis plans are not formally documented before data collection begins.
Moving from No Action to Emerging in Preregistration (Quant.)
To move from No Action to Emerging, take the following steps:
- Learn what preregistration is. Read about how preregistration improves research transparency and credibility in this guide.
- Start small. Try preregistering a simple project using templates from the Open Science Framework (OSF) or AsPredicted. These platforms guide you in recording your research questions, hypotheses, methods, and planned analyses before collecting data.
- Use the right platform for your field. If your study is health-related, register it with ClinicalTrials.gov, which is designed for clinical and medical research.
- Be clear about your study design. Use your preregistration to specify which parts of your study were planned in advance and which may be exploratory. This distinction increases clarity and credibility when you analyse and report results.
- Share your preregistration link. When publishing or presenting your research, include a link to your preregistration so others can verify your study’s design and analysis plan.
Emerging (Quant.)
Some studies are preregistered, usually in response to journal or funder requirements, but preregistrations tend to lack detail or consistency.
Moving from Emerging to Evolving in Preregistration (Quant.)
To move from Emerging to Evolving in preregistration for quantitative studies, focus on making preregistration routine, detailed, and transparent across all projects.
- Integrate preregistration into every quantitative study -- not only when required by journals or funders.
- Use detailed templates such as the OSF Preregistration Template or AsPredicted’s full template to describe research questions, sample size, exclusion criteria, and planned analyses.
- For experiments, also consider registering in the AEA RCT Registry, a widely used platform for randomised controlled trials in the social sciences.
- Justify your sample size by reporting how it was determined and conducting power analyses using free tools such as G*Power, GLIMMPSE, or OpenEpi.
- Document any deviations from the preregistered plan by updating the registration or logging changes with an explanatory note (see the OSF guide on updating registrations, useful paper).
- Include a direct link to your preregistration in publications and presentations (see example wording), and showcase your preregistrations by linking them in publications, presentations, your ORCID profile, CVs, and grant applications to signal your commitment to transparent and reflexive research.
Evolving (Quant.)
Preregistration is consistently applied to all hypothesis-driven studies, using public registries to provide detailed, transparent, and updatable records of study aims, methods, and analyses.
Moving from Evolving to Sustained in Preregistration (Quant.)
To move from Evolving to Sustained in preregistration, embed preregistration as a consistent part of your research workflow and begin shaping open research culture around you.
- Start using comprehensive preregistration templates that clearly distinguish planned (confirmatory) from exploratory analyses, such as the OSF Complex Preregistration Template or the EGAP Pre-Analysis Plan Guidelines.
- Always provide sample size justifications and power calculations using tools like G*Power, and clearly document all analytic decisions and exclusions.
- Begin broadening your preregistration practice to include secondary data analyses or complex designs (e.g. longitudinal, multi-level, or mixed-methods studies) using guides such as the OSF resource on preregistering non-traditional studies.
- Mentor and support others in your team or lab to preregister their work by sharing your templates, running short workshops, or using free materials such as the Center for Open Science.
- Normalise preregistration in your research community by making it expected in your lab or collaborations, and model transparency by including preregistration links in your papers, presentations, ORCID profile, CV, and grant applications.
Sustained (Quant.)
Preregistration is embedded in your research culture and applied systematically across all hypothesis-driven studies. You refine and innovate preregistration practices for complex designs, mentor colleagues in transparent research planning, and advocate for policies and incentives that make preregistration a standard expectation within your field.
Guidance for Sustained Level in Preregistration (Quant.)
Congratulations on reaching this level of practice. Preregistration is deeply embedded in your research culture and consistently applied across all hypothesis-driven studies. You contribute to advancing open research by mentoring others, influencing policy, and promoting transparent, reproducible science.
- Submit studies as Registered Reports, where your research plan is peer-reviewed before data collection (COS Registered Reports) and published in participating journals. See a usual webinar on Registered Reports
- Extend preregistration to complex designs, such as mixed-methods or qualitative components, using flexible guides like the OSF Preregistration for Qualitative Research.
- Mentor others and share your expertise by writing blogs, guides, or papers and leading workshops using the Center for Open Science training resources.
- Advocate for structural change by encouraging journals, funders, and institutions to recognise and reward preregistration practices.
- Enhance discoverability and impact by adding machine-readable metadata via DataCite, and tracking engagement using OpenAIRE or OSF Analytics.
- Showcase your preregistrations in your CV, grant applications, and public talks to demonstrate sustained commitment to open and transparent research.
