The Library can work with your team to encourage and support reproducible workflows and data management practices. Contact us at firstname.lastname@example.org
“the ability of a researcher to duplicate the results of a prior study using the same materials as were used by the original investigator. That is, a second researcher might use the same raw data to build the same analysis files and implement the same statistical analysis in an attempt to yield the same results…. Reproducibility is a minimum necessary condition for a finding to be believable and informative.”
- U.S. National Science Foundation (NSF) Subcommittee on Replicability in Science
Replicability: the ability of a researcher to duplicate the results of a prior study if the same procedures are followed but new data are collected (NSF)
Rigor: the strict application of the scientific method to ensure unbiased and well-controlled experimental design, methodology, analysis, interpretation and reporting of results (NIH)
Generalizability: whether the results of a study apply in other contexts or populations that differ from the original one (NSF)
Schloss, P. D. (2018). Identifying and overcoming threats to reproducibility, replicability, robustness, and generalizability in microbiome research. MBio, 9(3).
Bishop's “Four Horsemen of Irreproducibility Apocalypse” - Main factors that may lead to irreproducible or false positive research:
(2018). Checklists work to improve science. Nature, doi: https://doi.org/10.1038/d41586-018-04590-7 ; Bishop, D. (2019). Rein in the four horsemen of irreproducibility. Nature, 568(7753), 435-436.; Dumas-Mallet, E., Button, K. S., Boraud, T., Gonon, F., & Munafò, M. R. (2017). Low statistical power in biomedical science: a review of three human research domains. Royal Society Open Science, 4(2), 160254. ; Kerr, N. L. (1998). HARKing: Hypothesizing after the results are known. Personality and Social Psychology Review, 2(3), 196-217.