The Open Empirical Cycle for Hypothesis Evaluation in Psychology

In the last decade it has become clear that replicability of empirical psychological research should be better. Open science practices aim to enhance the transparency of research thereby both enabling others to reproduce the results presented in a paper and increasing the replicability of these results using new data. Examples of these practices include preregistration, publication of data and analyses, open access publications, and replication research. Although open science practices are gaining traction, they have rarely been placed in a broader epistemological context. To address this shortcoming, this paper introduces the open empirical cycle. It draws upon De Groot’s empirical cycle, a model of cumulative knowledge generation via scientific research. The open empirical cycle is a pragmatic guide for researchers that includes and links to open science practices. Adhering to the open empirical cycle, if only partly, will structure the scientific workflow and create awareness of the adverse consequences of deviations. Following the open empirical cycle increases the transparency, quality, trustworthiness, and replicability of research. The open empirical cycle presented in this paper focusses on hypothesis evaluation using quantitative data in psychology. However, it can straightforwardly be applied to hypothesis evaluation in other social and behavioral sciences and biomedical sciences. It brings together ideas from de Groot’s empirical cycle, traditional, and open research steps, key references, and open science tools, thereby providing a pragmatic, contemporary, and structured approach to hypothesis evaluation.