Does preregistration improve the credibility of research findings?

TL;DR

Preregistration aims to enhance research credibility by increasing transparency, but its effectiveness is limited unless combined with additional practices like data sharing and robustness checks, according to a critical review.

Contribution

This paper critically reviews 17 reasons supporting preregistration's role in credibility, highlighting its limitations and emphasizing the importance of comprehensive transparency practices.

Findings

Preregistration alone does not ensure research credibility.

Transparency in hypotheses and data sharing enhances credibility.

Robustness checks are crucial for credible research conclusions.

Abstract

Preregistration entails researchers registering their planned research hypotheses, methods, and analyses in a time-stamped document before they undertake their data collection and analyses. This document is then made available with the published research report to allow readers to identify discrepancies between what the researchers originally planned to do and what they actually ended up doing. This historical transparency is supposed to facilitate judgments about the credibility of the research findings. The present article provides a critical review of 17 of the reasons behind this argument. The article covers issues such as HARKing, multiple testing, p-hacking, forking paths, optional stopping, researchers' biases, selective reporting, test severity, publication bias, and replication rates. It is concluded that preregistration's historical transparency does not facilitate judgments about the credibility of research findings when researchers provide contemporary transparency in the form of (a) clear rationales for current hypotheses and analytical approaches, (b) public access to research data, materials, and code, and (c) demonstrations of the robustness of research conclusions to alternative interpretations and analytical approaches.