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A Generalised Linear Model Approach to Predict the Result of Research Evaluation

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Antonella Basso

    (Ca’ Foscari University of Venice, Department of Economics)

  • Giacomo di Tollo

    (Ca’ Foscari University of Venice, Department of Economics)

Abstract

Peer review is still used as the main tool for research evaluation, but its costly and time-consuming nature triggers a debate about the necessity to use, alternatively or jointly with it, bibliometric indicators. In this contribution we introduce an approach based on generalised linear models that jointly uses former peer-review and bibliometric indicators to predict the outcome of UK’s Research Excellence Framework (REF) 2014. We use the outcomes of the Research Assessment Exercise (RAE) 2008 as peer-review indicators and the departmental h-indices for the period 2008–2014 as bibliometric indicators. The results show that a joint use of bibliometric and peer-review indicators can be an effective tool to predict the research evaluation made by REF.

Suggested Citation

  • Antonella Basso & Giacomo di Tollo, 2017. "A Generalised Linear Model Approach to Predict the Result of Research Evaluation," Springer Books, in: Marco Corazza & Florence Legros & Cira Perna & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 29-41, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-50234-2_3
    DOI: 10.1007/978-3-319-50234-2_3
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