Preregistration

FINISHED PROJECTS ABOUT PREREGISTRATION:

Van den Akker, O. R., Weston, S., Campbell. L., Chopik, W., Damian, R., Davis-Kean, P., Hall, A., Kosie, J., Kruse, E., Olsen, J., Ritchie, S., Valentine, K., Van ‘t Veer, A., & Bakker, M. (under review). Preregistration of secondary data analysis: A template and tutorial.

In this tutorial, we present a template specifically designed for the preregistration of secondary data analyses, and provide comments and a practical example that may help with using the template effectively.

Preprint

Data and materials

Bakker, M., Veldkamp, C. L. S., Van den Akker, O. R., van Assen, M. A. L. M., Crompvoets, E. A. V., Ong, H. H., & Wicherts, J. M. (under review). We have the (1-b)! Requirements in preregistrations and IRB proposals promote formal power analyses.

We investigated whether the statistical power of a study is higher when researchers are asked to make a formal power analysis before collecting data. We compared the sample size descriptions from two sources: (i) a sample of preregistrations created according to the guidelines for the Center for Open Science Preregistration Challenge (PCRs) and a sample of institutional review board (IRB) proposals from Tilburg School of Behavior and Social Sciences in which a power analysis is advised, and (ii) a sample of preregistrations created according to the guidelines for Open Science Framework Standard Pre-Data Collection Registrations (SPRs) in which no guidance on sample size planning is given. We found that PCRs and IRBs (72%) more often included sample size decisions based on power analyses than the SPRs (45%). However, this did not result in larger planned sample sizes.

Preprint

Data and materials

Olmo van den Akker
Olmo van den Akker

Olmo van den Akker is a PhD-student at the Meta-Research center at Tilburg University, where he is currently studying the efficacy of preregistration and the way researchers interpret statistical results.