The Replication Database: Documenting the Replicability of Psychological Science

Abstract

In psychological science, replicability—repeating a study with a new sampleachieving consistent results (Parsons et al., 2022)—is critical for affirming the validity of scientific findings. Despite its importance, replication efforts are few and far between in psychological science with many attempts failing to corroborate past findings. This scarcity, compounded by the difficulty in accessing replication data, jeopardizes the efficient allocation of research resources and impedes scientific advancement. Addressing this crucial gap, we present the Replication Database (https://metaanalyses.shinyapps.io/replicationdatabase/), a novel platform hosting 1,239 original findings paired with replication findings. The infrastructure of this database allows researchers to submit, access, and engage with replication findings. The database makes replications visible, easily findable via a graphical user interface, and tracks replication rates across various factors, such as publication year or journal. This will facilitate future efforts to evaluate the robustness of psychological research.

dynConfiR: The R package for sequential sampling models of decision confidence

“…For new experiments, we recommend using pilot data to infer suitable exclusion criteria because different experimental paradigms produce different response time distributions. In light of ongoing replication issues in psychology (Röseler et al, 2024), we recommend to pre-register exclusion criteria and check whether results are robust concerning the specific choice of exclusion criteria (Wagenmakers et al, 2012).…”