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Articles

Rethinking the Funding Line at the Swiss National Science Foundation: Bayesian Ranking and Lottery

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Pages 110-121 | Received 19 Feb 2021, Accepted 31 May 2022, Published online: 12 Jul 2022

References

  • Adam, D. (2019), “Science Funders Gamble on Grant Lotteries,” Nature, 575, 574–575. DOI: 10.1038/d41586-019-03572-7.
  • Alberts, B., Kirschner, M. W., Tilghman, S., and Varmus, H. (2014), “Rescuing US Biomedical Research from its Systemic Flaws,” Proceedings of the National Academy of Sciences of the United States of America, 111, 5773–5777. DOI: 10.1073/pnas.1404402111..
  • Austrian Research Fund. (2020), “1000 Ideas Programme,” Available at https://www.fwf.ac.at/en/research-funding/fwf-programmes/1000-ideas-programme.
  • Bates, D., Maechler, M., Bolker, B. M., and Walker, S. C. (2015), “Fitting Linear Mixed-Effects Models Using lme4,” Journal of Statistical Software, 67, 1–48. DOI: 10.18637/jss.v067.i01..
  • Berger, J., and Deely, J. (1988), “A Bayesian-Approach to Ranking and Selection of Related Means with Alternatives to Analysis-of-Variance Methodology,” Journal of the American Statistical Association, 83, 364–373. DOI: 10.2307/2288851..
  • Bieri, M., Roser, K., Heyard, R., and Egger, M. (2021), “Face-to-face Panel Meetings Versus Remote Evaluation of Fellowship Applications: Simulation Study at the Swiss National Science Foundation,” BMJ Open, 11, e047386. DOI: 10.1136/bmjopen-2020-047386.
  • Bland, J. M., and Altman, D. G. (1999), “Measuring Agreement in Method Comparison Studies,” Statistical Methods in Medical Research, 8, 135–160. DOI: 10.1177/096228029900800204.
  • Bürkner, P.-C. (2018), “Advanced Bayesian Multilevel Modeling with the R Package brms,” R Journal, 10, 395–411. DOI: 10.32614/RJ-2018-017.
  • Bromham, L., Dinnage, R., and Hua, X. (2016), “Interdisciplinary Research has Consistently Lower Funding Success,” Nature, 534, 684–687. DOI: 10.1038/nature18315.
  • Cao, J., Stokes, S. L., and Zhang, S. (2010), “A Bayesian Approach to Ranking and Rater Evaluation,” Journal of Educational and Behavioral Statistics, 35, 194–214. DOI: 10.3102/1076998609353116..
  • Cicchetti, D. (1993), “The Reliability of Peer-Review for Manuscript and Grant Submissions – Its Like Deja-Vu All Over Again – Authors Response,” Behavioral and Brain Sciences, 16, 401–403. DOI: 10.1017/S0140525X0003079X..
  • Cole, S., Cole, J. R., and Simon, G. A. (1981), “Chance and Consensus in Peer Review,” Science (New York, N.Y.), 214, 881–886. DOI: 10.1126/science.7302566.
  • DORA. (2019), “DORA – San Francisco Declaration on Research Assessment,” Available at https://sfdora.org/.
  • Fang, F. C., and Casadevall, A. (2016), “Research Funding: The Case for a Modified Lottery (vol 7, e00422, 2016),” Mbio, 7, e00694–16. DOI: 10.1128/mBio.00694-16.
  • Fang, F. C., Bowen, A., and Casadevall, A. (2016), “NIH Peer Review Percentile Scores are Poorly Predictive of Grant Productivity,” Elife, 5, e13323. DOI: 10.7554/eLife.13323..
  • Fogelholm, M., Leppinen, S., Auvinen, A., Raitanen, J., Nuutinen, A., and Väänänen, K. (2012), “Panel Discussion does not Improve Reliability of Peer Review for Medical Research Grant Proposals,” Journal of Clinical Epidemiology, 65, 47–52. DOI: 10.1016/j.jclinepi.2011.05.001.
  • Gelman, A. (2006), “Prior Distributions for Variance Parameters in Hierarchical Models (comment on article by Browne and Draper),” Bayesian Analysis, 1, 515–534. DOI: 10.1214/06-BA117A..
  • Gelman, A., and Rubin, D. B. (1992), “Inference from Iterative Simulation Using Multiple Sequences,” Statistical Science, 7, 457–472. DOI: 10.1214/ss/1177011136..
  • Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B. (2014), Bayesian Data Analysis (3rd ed.), New York, NY: Chapman and Hall/CRC. DOI: 10.1201/b16018.
  • Goldstein, H., and Spiegelhalter, D. J. (1996), “League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance,” Journal of the Royal Statistical Society, Series A, 159, 385–443. DOI: 10.2307/2983325..
  • Guthrie, S., Ghiga, I., and Wooding, S. (2018), “What do we know about Grant Peer Review in the Health Sciences?” F1000Research, 6, 1335. DOI: 10.12688/f1000research.11917.2.
  • Guthrie, S., Rodriguez Rincon, D., McInroy, G., Ioppolo, B., and Gunashekar, S. (2019), “Measuring Bias, Burden and Conservatism in Research Funding Processes,” F1000Research, 8, 851. DOI: 10.12688/f1000research.19156.1..
  • Harman, G. (1998), “The Management of Quality Assurance: A Review of International Practice,” Higher Education Quarterly, 52, 345–364. DOI: 10.1111/1468-2273.00104..
  • Hedeker, D., Mermelstein, R. J., and Demirtas, H. (2008), “An Application of a Mixed-Effects Location Scale Model for Analysis of Ecological Momentary Assessment (EMA) Data,” Biometrics, 64, 627–634. DOI: 10.1111/j.1541-0420.2007.00924.x.
  • Jayasinghe, U. W., Marsh, H. W., and Bond, N. (2003), “A Multilevel Cross-Classified Modelling Approach to Peer Review of Grant Proposals: The Effects of Assessor and Researcher Attributes on Assessor Ratings,” Journal of the Royal Statistical Society, Series A, 166, 279–300. DOI: 10.1111/1467-985x.00278..
  • Johnson, V. E. (2008), “Statistical Analysis of the National Institutes of Health Peer Review System,” Proceedings of the National Academy of Sciences of the United States of America, 105, 11076–11080. DOI: 10.1073/pnas.0804538105.
  • Kaatz, A., Gutierrez, B., and Carnes, M. (2014), “Threats to Objectivity in Peer Review: The Case of Gender,” Trends in Pharmacological Sciences, 35, 371–373. DOI: 10.1016/j.tips.2014.06.005.
  • Kaplan, D., Lacetera, N., and Kaplan, C. (2008), “Sample Size and Precision in NIH Peer Review,” PloS One, 3, e2761. DOI: 10.1371/journal.pone.0002761.
  • Klaus, B., and Alamo, D. D. (2018), “Talent Identification at the Limits of Peer Review: An Analysis of the EMBO Postdoctoral Fellowships Selection Process,” bioRxiv, 481655. DOI: 10.1101/481655..
  • Laird, N. M., and Louis, T. A. (1989), “Empirical Bayes Ranking Methods,” Journal of Educational Statistics, 14, 29–46. DOI: 10.2307/1164724..
  • Lingsma, H. F., Steyerberg, E. W., Eijkemans, M. J. C., Dippel, D. W. J., Scholte Op Reimer, W. J. M., Van Houwelingen, H. C., and The Netherlands Stroke Survey Investigators. (2010), “Comparing and Ranking Hospitals based on Outcome: Results from The Netherlands Stroke Survey,” QJM: An International Journal of Medicine, 103, 99–108. DOI: 10.1093/qjmed/hcp169..
  • Liu, M., Choy, V., Clarke, P., Barnett, A., Blakely, T., and Pomeroy, L. (2020), “The Acceptability of Using a Lottery to Allocate Research Funding: A Survey of Applicants,” Research Integrity and Peer Review, 5, 3. DOI: 10.1186/s41073-019-0089-z.
  • Lucy, L., Freedman, J. E., Becker, L. B., Mehta, N. N., and Liscum, L. (2017), “Peer Review Practices for Evaluating Biomedical Research Grants: A Scientific Statement From the American Heart Association,” Circulation Research, 121, e9–e19. DOI: 10.1161/RES.0000000000000158.
  • Mayo, N. E., Brophy, J., Goldberg, M. S., Klein, M. B., Miller, S., Platt, R. W., and Ritchie, J. (2006), “Peering at Peer Review Revealed High Degree of Chance Associated with Funding of Grant Applications,” Journal of Clinical Epidemiology, 59, 842–848. DOI: 10.1016/j.jclinepi.2005.12.007.
  • Morris, T. P., White, I. R., and Crowther, M. J. (2019), “Using Simulation Studies to Evaluate Statistical Methods,” Statistics in Medicine, 38, 2074–2102. DOI: 10.1002/sim.8086.
  • Plummer, M. (2019), “‘rjags’. Bayesian Graphical Models using MCMC.” Available at https://CRAN.R-project.org/package=rjags.
  • Salanti, G., Ades, A. E., and Ioannidis, J. P. A. (2011), “Graphical Methods and Numerical Summaries for Presenting Results from Multiple-Treatment Meta-Analysis: An Overview and Tutorial,” Journal of Clinical Epidemiology, 64, 163–171. DOI: 10.1016/j.jclinepi.2010.03.016.
  • Scheiner, S. M., and Bouchie, L. M. (2013), “The Predictive Power of NSF Reviewers and Panels,” Frontiers in Ecology and the Environment, 11, 406–407. DOI: 10.1890/13.WB.017.
  • Severin, A., and Egger, M. (2020), “Research on Research Funding: An Imperative for Science and Society,” British Journal of Sports Medicine, 55, 648–649. DOI: 10.1136/bjsports-2020-103340.
  • Severin, A., Martins, J., Heyard, R., Delavy, F., Jorstad, A., and Egger, M. (2020), “Gender and other Potential Biases in Peer Review: Cross-Sectional Analysis of 38 250 External Peer Review Reports,” Bmj Open, 10, e035058. DOI: 10.1136/bmjopen-2019-035058.
  • Shrout, P. E., and Fleiss, J. L. (1979), “Intraclass Correlations: Uses in Assessing Rater Reliability,” Psychological Bulletin, 86, 420–428. DOI: 10.1037/0033-2909.86.2.420..
  • van der Lee, R., and Ellemers, N. (2015), “Gender Contributes to Personal Research Funding Success in The Netherlands,” Proceedings of the National Academy of Sciences of the United States of America, 112, 12349–12353. DOI: 10.1073/pnas.1510159112.
  • van Houwelingen, H. C., Brand, R., and Louis, T. A. (2009), “Empirical Bayes Methods for Monitoring Health Care Quality,” arXiv:2009.03058 [stat].
  • Volkswagen Foundation. (2017), “Experiment! – In Search of Bold Research Ideas,” Available at https://www.volkswagenstiftung.de/en/funding/our-funding-portfolio-at-a-glance/experiment.