A lot of new interesting work is being done on questions of reproducibility across the sciences by diverse researchers from different disciplines. Here we share 2-3 papers every month that come from what Project Members are reading. Have a suggestion? Let us know.
Finkel, E.J., P.W. Eastwick, and H.T. Reis. 2017. Replicability and other features of a high-quality science: Toward a balanced and empirical approach. Journal of Personality and Social Psychology 113(2):244-253.
Nichols, J.D., M K. Oli, W.L. Kendall, and G.S. Boomer. 2021. A better approach for dealing with reproducibility and replicability in science. Proceedings of the National Academy of Sciences 118(7):e2100769118.
de Haas, B. 2021. What my retraction taught me. Nature 589:331.
Flis, I. 2019. Psychologists psychologizing scientific psychology: An epistemological reading of the replication crisis. Theory & Psychology 29(2):158–181.
Schwarzkopf, S. 2020. When the hole changes the pigeon (blog post related to de Haas 2021).
Bakker M., C.L.S Veldkamp, M.A.L.M van Assen, E.A.V Crompvoets, H.H. Ong, B.A. Nosek, et al. 2020. Ensuring the quality and specificity of preregistrations. PLoS Biology 18(12):e3000937.
Romero, F. 2020. The division of replication labor. Philosophy of Science 87:1014-1025.
Baker, Z.G., E.-A. Gentzis, E.M. Watlington, S. Castejon, W.E. Petit, M. Britton, S. Haddad, A.M. DiBello, L.M. Rodriguez, J.L. Derrick and C.R. Knee. 2020. Reflections on a registered report replicating a body of dyadic cross-sectional research. Personal Relationships.
Simonsohn, U., J.P. Simmons, and L.D. Nelson. 2020. Specification curve analysis. Nature Human Behaviour 4:1208–1214.
da Silva Frost, A. and A. Ledgerwood A. 2020. Calibrate your confidence in research findings: A tutorial on improving research methods and practices. Journal of Pacific Rim Psychology 14:e14.
Mejlgaard, N., L.M. Bouter, G. Gaskell, P. Kavouras, N. Allum, et al. 2020. Research integrity: nine ways to move from talk to walk. Nature 586:358-360.
Belikov, A.V. A. Rzhetsky, and J. Evans. 2020. Detecting signal from science: The structure of research communities and prior knowledge improves prediction of genetic regulatory experiments. arXiv:2008.09985
de Menard, A. 2020. What's Wrong with Social Science and How to Fix It: Reflections After Reading 2578 Papers. Fantastic Anachronism
Gordon, M., D. Viganola, M. Bishop, Y. Chen, A. Dreber, B. Goldfedder, F. Holzmeister, M. Johannesson, Y. Liu, C. Twardy, J. Wang, and T. Pfeiffer. 2020. Are replication rates the same across academic fields? Community forecasts from the DARPA SCORE programme. Royal Society Open Science 7(7):200566.
Heesen, R. and L.K. Bright. 2020. Is peer review a good idea? The British Journal for the Philosophy of Science: axz029.
Jin, J., N. Agarwala, P. Kundu, Y. Wang, R. Zhao, and N. Chatterjee. 2020. Transparency, reproducibility, and validation of COVID-19 projection models. COVID-19: School of Public Health Expert Insights. Johns Hopkins Bloomberg School of Public Health.
Moher, D. L. Bouter, S. Kleinert, P. Glasziou, M.H. Sham, V. Barbour, A.-M. Coriat, N. Foeger, and Ul Dirnagl. 2020. The Hong Kong Principles for assessing researchers: Fostering research integrity. PLoS Biology 18(7):e3000737.
Adda, J., C. Decker, and M. Ottaviani. 2020. P-hacking in clinical trials and how incentives shape the distribution of results across phases. Proceedings of the National Academy of Sciences 117:13386-13392.
Botvinik-Nezer, R., F. Holzmeister, C. F. Camerer, A. Dreber, J. Huber, et al. 2020. Variability in the analysis of a single neuroimaging dataset by many teams. Nature 582:84-88.
Ofosu, G.K., and D.N. Posner. 2020. Do pre-analysis plans hamper publication? AEA Papers and Proceedings 110:70-74.
Gilmore, R.O., P.M, Cole, S. Verma, M.A. Van Aken, and C.M. Worthman. 2020. Advancing scientific integrity, transparency, and openness in child development research: challenges and possible solutions. Child Development Perspectives 14:9-14.
London, A.J. and J. Kimmelman. 2020. Against pandemic research exceptionalism. Science 368:476-477.
Wilkinson, M., M. Dumontier, I. Aalbersberg, et al. 2016. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3:160018.
Nosek, B.A. and T.M. Errington. 2020. What is replication? PLoS Biology 18(3): e3000691.
Tiokhin, L., J. Hackman, S. Munira, K. Jesmin, and D. Hruschka. 2019. Generalizability is not optional: insights from a cross-cultural study of social discounting. Royal Society Open Science 6: 181386.
Wilson, B.M., C.R. Harris, J.T. Wixted. 2020. Science is not a signal detection problem. Proceedings of the National Academy of Sciences 117(11):5559–5567.
Laskowski, K. 2020. What to do when you don’t trust your data anymore.
Lundwall, R.A. 2019. Changing institutional incentives to foster sound scientific practices: One department. Infant Behavior and Development 55:69-76.
Koroshetz, W.J., S. Behrman, C.J. Brame, et al. 2020. Research culture: Framework for advancing rigorous research. eLife 9:e55915.
Milton, M.J.T. and A. Possolo. 2019. Trustworthy data underpin reproducible research. Nature Physics 16:117–119.
Bryan, C.J., D.S. Yeager, and J.M. O'Brien. 2019. Replicator degrees of freedom allow publication of misleading failures to replicate. Proceedings of the National Academy of Sciences 116:25535–25545.
Feest, U. 2019. Why replication is overrated. Philosophy of Science 86:895–905.
Krummel, M., C. Blish, M. Kuhns, K. Cadwell, A. Oberst, A. Goldrath, K.M. Ansel, J. Chi, R. O'Connell, E.J. Wherry, M. Pepper, and The Future Immunology Consortium. 2019. Universal principled review: a community-driven method to improve peer review. Cell 179:1441–1445