References
Akker, O. R. van den, Weston, S., Campbell, L., Chopik, B., Damian, R., Davis-Kean, P., Hall, A., Kosie, J., Kruse, E., Olsen, J., et al. (2021). Preregistration of secondary data analysis: A template and tutorial. Meta-Psychology, 5. https://doi.org/10.15626/MP.2020.2625
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01
Bosnjak, M., Fiebach, C. J., Mellor, D., Mueller, S., O’Connor, D. B., Oswald, F. L., & Sokol-Chang, R. I. (2021). A template for preregistration of quantitative research in psychology: Report of the joint psychological societies preregistration task force. American Psychologist. https://doi.org/10.1037/amp0000879
Buchanan, E. M., Crain, S. E., Cunningham, A. L., Johnson, H. R., Stash, H., Papadatou-Pastou, M., Isager, P. M., Carlsson, R., & Aczel, B. (2021). Getting started creating data dictionaries: How to create a shareable data set. Advances in Methods and Practices in Psychological Science, 4(1), 2515245920928007. https://doi.org/10.1177/2515245920928007
Condon, D. M., Arnal, J., Binion, G., Brown, B., & Corker, K. S. (2020). Not one but many models of open-access publishing. APS Observer, 33(9). https://www.psychologicalscience.org/observer/not-one-but-many-models-of-open-access-publishing
Corker, K. S. (2021). An open science workflow for more credible, rigorous research.
Crüwell, S., Doorn, J. van, Etz, A., Makel, M. C., Moshontz, H., Niebaum, J. C., Orben, A., Parsons, S., & Schulte-Mecklenbeck, M. (2019). Seven easy steps to open science: An annotated reading list. Zeitschrift für Psychologie, 227(4), 237.
DuBois, J. M., Strait, M., & Walsh, H. (2018). Is it time to share qualitative research data? Qualitative Psychology, 5(3), 380.
Fry, N., Marshal, H., & Mellins-Cohen, T. (2019). In praise of preprints. Microbial Genomics, 5. https://doi.org/10.1099/mgen.0.000259
Gollwitzer, M., Abele-Brehm, A., Fiebach, C., Ramthun, R., Scheel, A. M., Schönbrodt, F. D., & Steinberg, U. (2020). Data management and data sharing in psychological science: Revision of the DGPs recommendations. PsyArXiv. https://doi.org/10.31234/osf.io/24ncs
Haroz, S. (2022). Comparison of preregistration platforms. MetaArXiv. https://doi.org/10.31222/osf.io/zry2u
Holcombe, A. O. (2019). Contributorship, not authorship: Use CRediT to indicate who did what. Publications, 7(3), 48. https://doi.org/10.3390/publications7030048
Horstmann, K. T., Arslan, R. C., & Greiff, S. (2020). Generating codebooks to ensure the independent use of research data: Some guidelines. https://doi.org/10.1027/1015-5759/a000620
Kathawalla, U.-K., Silverstein, P., & Syed, M. (2021). Easing into open science: A guide for graduate students and their advisors. Collabra: Psychology, 7(1).
Kazak, A. E. (2018). Journal article reporting standards. https://doi.org/10.1037/amp0000263
Larivière, V., Pontille, D., & Sugimoto, C. R. (2021). Investigating the division of scientific labor using the contributor roles taxonomy (CRediT). Quantitative Science Studies, 2(1), 111–128. https://doi.org/10.1162/qss_a_00097
Meyer, M. N. (2018). Practical tips for ethical data sharing. Advances in Methods and Practices in Psychological Science, 1(1), 131–144. https://doi.org/10.1177/2515245917747656
Moshontz, H., Binion, G., Walton, H., Brown, B. T., & Syed, M. (2021). A guide to posting and managing preprints. Advances in Methods and Practices in Psychological Science, 4(2), 25152459211019948. https://doi.org/10.1177/25152459211019948
Parsons, S., Azevedo, F., Elsherif, M. M., Guay, S., Shahim, O. N., Govaart, G. H., Norris, E., O’mahony, A., Parker, A. J., Todorovic, A., et al. (2022). A community-sourced glossary of open scholarship terms. Nature Human Behaviour, 6(3), 312–318.
R Core Team. (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
Vable, A. M., Diehl, S. F., & Glymour, M. M. (2021). Code review as a simple trick to enhance reproducibility, accelerate learning, and improve the quality of your team’s research. American Journal of Epidemiology, 190(10), 2172–2177. https://doi.org/10.1093/aje/kwab092
Weston, S. J., Ritchie, S. J., Rohrer, J. M., & Przybylski, A. K. (2019). Recommendations for increasing the transparency of analysis of preexisting data sets. Advances in Methods and Practices in Psychological Science, 2(3), 214–227. https://doi.org/10.1177/2515245919848684