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Measuring university quality

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  • Christopher Claassen

    (University of Essex)

Abstract

This paper uses a Bayesian hierarchical latent trait model, and data from eight different university ranking systems, to measure university quality. There are five contributions. First, I find that ratings tap a unidimensional, underlying trait of university quality. Second, by combining information from different systems, I obtain more accurate ratings than are currently available from any single source. And rather than dropping institutions that receive only a few ratings, the model simply uses whatever information is available. Third, while most ratings focus on point estimates and their attendant ranks, I focus on the uncertainty in quality estimates, showing that the difference between universities ranked 50th and 100th, and 100th and 250th, is insignificant. Finally, by measuring the accuracy of each ranking system, as well as the degree of bias toward universities in particular countries, I am able to rank the rankings.

Suggested Citation

  • Christopher Claassen, 2015. "Measuring university quality," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 793-807, September.
    • Handle: RePEc:spr:scient:v:104:y:2015:i:3:d:10.1007_s11192-015-1584-8
    DOI: 10.1007/s11192-015-1584-8
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    Cited by:

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    2. Csóka, Imola & Sebestyén, Géza & Neszveda, Gábor, 2019. "Tudományos teljesítmény mérése a magyar felsőoktatás gazdasági képzéseiben [Measuring scientific performance of business and economics faculties in Hungarian higher education]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 751-770.
    3. Elisabeth Maria Schlagberger & Lutz Bornmann & Johann Bauer, 2016. "At what institutions did Nobel laureates do their prize-winning work? An analysis of biographical information on Nobel laureates from 1994 to 2014," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 723-767, November.
    4. Lutz Bornmann & Alexander Butz & Klaus Wohlrabe, 2018. "What are the top five journals in economics? A new meta-ranking," Applied Economics, Taylor & Francis Journals, vol. 50(6), pages 659-675, February.
    5. 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.
    6. Wenqiang Fan & Qinghui Liu, 2016. "Open scholarship ranking of Chinese research universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 673-691, August.

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