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Funnel plots for visualizing uncertainty in the research performance of institutions

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  • Abramo, Giovanni
  • D’Angelo, Ciriaco Andrea
  • Grilli, Leonardo

Abstract

Research performance values are not certain. Performance indexes should therefore be accompanied by uncertainty measures, to establish whether the performance of a unit is truly outstanding and not the result of random fluctuations. In this work we focus on the evaluation of research institutions on the basis of average individual performance, where uncertainty is inversely related to the number of research staff. We utilize the funnel plot, a tool originally developed in meta-analysis, to measure and visualize the uncertainty in the performance values of research institutions. As an illustrative example, we apply the funnel plot to represent the uncertainty in the assessed research performance for Italian universities active in biochemistry.

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  • Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Grilli, Leonardo, 2015. "Funnel plots for visualizing uncertainty in the research performance of institutions," Journal of Informetrics, Elsevier, vol. 9(4), pages 954-961.
  • Handle: RePEc:eee:infome:v:9:y:2015:i:4:p:954-961
    DOI: 10.1016/j.joi.2015.08.006
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    References listed on IDEAS

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    1. Giovanni Abramo & Ciriaco Andrea D'Angelo & Flavia Di Costa, 2008. "Assessment of sectoral aggregation distortion in research productivity measurements," Research Evaluation, Oxford University Press, vol. 17(2), pages 111-121, June.
    2. Schneider, Jesper W., 2013. "Caveats for using statistical significance tests in research assessments," Journal of Informetrics, Elsevier, vol. 7(1), pages 50-62.
    3. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2012. "The dispersion of research performance within and between universities as a potential indicator of the competitive intensity in higher education systems," Journal of Informetrics, Elsevier, vol. 6(2), pages 155-168.
    4. Alexander Karlsson & Björn Hammarfelt & H. Joe Steinhauer & Göran Falkman & Nasrine Olson & Gustaf Nelhans & Jan Nolin, 2015. "Modeling uncertainty in bibliometrics and information retrieval: an information fusion approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2255-2274, March.
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    6. Ciriaco Andrea D'Angelo & Cristiano Giuffrida & Giovanni Abramo, 2011. "A heuristic approach to author name disambiguation in bibliometrics databases for large-scale research assessments," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(2), pages 257-269, February.
    7. Lutz Bornmann & Rüdiger Mutz & Werner Marx & Hermann Schier & Hans‐Dieter Daniel, 2011. "A multilevel modelling approach to investigating the predictive validity of editorial decisions: do the editors of a high profile journal select manuscripts that are highly cited after publication?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(4), pages 857-879, October.
    8. Ciriaco Andrea D'Angelo & Cristiano Giuffrida & Giovanni Abramo, 2011. "A heuristic approach to author name disambiguation in bibliometrics databases for large‐scale research assessments," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(2), pages 257-269, February.
    9. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2012. "Revisiting the scaling of citations for research assessment," Journal of Informetrics, Elsevier, vol. 6(4), pages 470-479.
    10. Andrea Bonaccorsi & Cinzia Daraio, 2005. "Exploring size and agglomeration effects on public research productivity," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(1), pages 87-120, March.
    11. Lutz Bornmann & Rüdiger Mutz & Hans-Dieter Daniel, 2013. "Multilevel-statistical reformulation of citation-based university rankings: The Leiden ranking 2011/2012," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(8), pages 1649-1658, August.
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    13. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Rosati, Francesco, 2013. "The importance of accounting for the number of co-authors and their order when assessing research performance at the individual level in the life sciences," Journal of Informetrics, Elsevier, vol. 7(1), pages 198-208.
    14. Sheila M. Bird & Cox Sir David & Vern T. Farewell & Goldstein Harvey & Holt Tim & Smith Peter C., 2005. "Performance indicators: good, bad, and ugly," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(1), pages 1-27, January.
    15. Ludo Waltman & Clara Calero-Medina & Joost Kosten & Ed C.M. Noyons & Robert J.W. Tijssen & Nees Jan Eck & Thed N. Leeuwen & Anthony F.J. Raan & Martijn S. Visser & Paul Wouters, 2012. "The Leiden ranking 2011/2012: Data collection, indicators, and interpretation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2419-2432, December.
    16. Colliander, Cristian & Ahlgren, Per, 2011. "The effects and their stability of field normalization baseline on relative performance with respect to citation impact: A case study of 20 natural science departments," Journal of Informetrics, Elsevier, vol. 5(1), pages 101-113.
    17. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2011. "Assessing the varying level of impact measurement accuracy as a function of the citation window length," Journal of Informetrics, Elsevier, vol. 5(4), pages 659-667.
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    1. Abramo, Giovanni & D’Angelo, Andrea Ciriaco & Grilli, Leonardo, 2016. "From rankings to funnel plots: The question of accounting for uncertainty when assessing university research performance," Journal of Informetrics, Elsevier, vol. 10(3), pages 854-862.
    2. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Rosati, Francesco, 2016. "A methodology to measure the effectiveness of academic recruitment and turnover," Journal of Informetrics, Elsevier, vol. 10(1), pages 31-42.

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