Preregistration is the practice of publicly specifying a study’s hypotheses, methods and analysis plan before any data are collected or examined. By fixing these decisions in advance and time-stamping them, preregistration draws a clear line between confirmatory tests planned ahead of time and exploratory analyses discovered along the way — a distinction that curbs questionable research practices and strengthens reproducibility. The plan is registered publicly so that it cannot be quietly revised once results are known, which is what gives the time stamp its force.
The problem it addresses is well documented. When analysis choices are made after seeing the data, researchers can — often unconsciously — select the specification that yields a significant result, a practice known as p-hacking. Separately, studies with positive findings are more likely to be published than null results, producing publication bias that distorts the literature. Preregistration tackles the first; Registered Reports tackle both. The two practices grew out of the wider reproducibility movement, which found that a worrying share of published findings did not hold up when independent teams tried to repeat them — a problem driven in part by exactly these analytic and publication pressures. By making the research plan public and time-stamped before results exist, both practices restore a clear distinction between what was predicted and what was merely found.
What preregistration involves
A preregistration typically states the research question, the hypotheses, the sample size and stopping rule, the variables, and the precise analysis plan, lodged in a public registry with a time stamp. Templates and registries hosted on the Open Science Framework (OSF), maintained by the Center for Open Science, make this routine. Clinical trials have long used dedicated public registries for the same reason, and the practice has since spread across the social and life sciences. Because the plan is fixed, readers can verify that the reported confirmatory analysis is the one that was promised, and exploratory work is labelled as such rather than dressed up as a prediction. A good preregistration is specific enough that a third party could, in principle, run the planned analysis without further instruction.
Confirmatory versus exploratory research
The conceptual heart of preregistration is the distinction between confirmatory and exploratory research. Confirmatory research tests a specific, pre-stated hypothesis with a pre-specified analysis; its statistical guarantees — including the meaning of a p-value — depend on the analysis having been fixed in advance. Exploratory research, by contrast, searches the data for patterns and generates new hypotheses; it is valuable and necessary, but its findings are provisional and must be confirmed in fresh data. Problems arise when exploratory results are dressed up as confirmatory ones, lending them a false air of statistical rigour. Preregistration keeps the two honest by recording, with a time stamp, exactly which analyses were planned. Anything beyond that plan is legitimate exploration, simply labelled as such rather than presented as a prediction that came true.
Registered Reports go further
A Registered Report is a publication format in which the introduction, methods and analysis plan are peer-reviewed before data collection. If the question and design are judged sound, the journal grants in-principle acceptance — a commitment to publish the completed study regardless of whether the results are positive, negative or null, provided the authors follow the approved protocol. This decouples the publication decision from the outcome, directly attacking publication bias. A useful side effect is that reviewers can improve a study before it is run, when flaws can still be fixed, rather than critiquing an unchangeable design after the fact. This shifts peer review from gatekeeping to genuine quality improvement, and reduces the waste of running studies whose weaknesses only surface at submission.
How each curbs bias
| Practice | Reviewed before data? | Mainly curbs |
|---|---|---|
| Preregistration | No (registry only) | p-hacking, hidden analytic flexibility |
| Registered Report | Yes (stage-one peer review) | p-hacking and publication bias |
The shared mechanism is timing: committing to decisions before outcomes are known removes the temptation, and the opportunity, to reshape a study around a desired result. This complements the rigour built into experimental designs such as the randomised controlled trial, where preregistered protocols make ITT and primary-outcome commitments verifiable.
The two-stage Registered Report workflow
What makes Registered Reports distinctive is their two-stage review. At stage one, reviewers evaluate the question’s importance and the soundness of the proposed methods and analysis before any data exist; sound proposals earn in-principle acceptance. At stage two, after the study is run, reviewers check that the authors followed the approved protocol and that conclusions match the registered plan — but they do not get to reject the paper simply because the results were null or unexciting. This sequencing is what severs the link between a study’s outcome and its publishability.
| Stage | What is reviewed | Decision |
|---|---|---|
| Stage one | Question, methods, analysis plan | In-principle acceptance |
| Data collection | Conducted per approved protocol | — |
| Stage two | Adherence to plan, valid conclusions | Publication regardless of result |
How they curb publication bias and p-hacking
Publication bias arises when the literature over-represents positive findings because null results are harder to publish. By guaranteeing publication at stage one, Registered Reports ensure null and negative results enter the record, giving a more honest picture of the evidence. P-hacking — selecting the analysis that happens to reach significance — is curbed by both formats, because the analytic decisions are fixed and public before the data are seen. Together these mechanisms protect the integrity of confirmatory claims, much as the pre-specified primary outcomes of a randomised controlled trial protect its causal conclusions.
Benefits and honest limits
Preregistration improves transparency, makes exploratory work explicit and supports the reproducibility goals at the heart of the research lifecycle. It does not forbid exploration; it simply requires that exploratory findings be reported as such. Deviations from a plan are permitted when justified and disclosed, and preregistration cannot by itself guarantee a study is well designed — a poor plan, preregistered, is still a poor plan. Used alongside the standardised documentation described in the CASRAI dictionary and our guidance for authors, it makes the chain from hypothesis to result auditable.
Frequently asked questions
What is the difference between preregistration and a Registered Report?
Preregistration time-stamps a plan in a public registry but is not peer-reviewed in advance. A Registered Report adds stage-one peer review and in-principle acceptance before data are collected, committing the journal to publish the results.
How does preregistration reduce p-hacking?
By fixing the hypotheses and analysis plan before the data are seen, it removes the ability to choose, after the fact, the specification that happens to produce a significant result.
Does preregistration ban exploratory analysis?
No. Exploration is encouraged, but it must be reported as exploratory rather than presented as a pre-planned confirmatory test. Justified deviations from the plan are allowed when disclosed.
What is the Center for Open Science’s role?
The Center for Open Science maintains the Open Science Framework, which hosts preregistration templates and registries and supports the Registered Reports format adopted by many journals.
