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Accounting for the uncertainty in the evaluation of percentile ranks

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  • Loet Leydesdorff

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  • Loet Leydesdorff, 2012. "Accounting for the uncertainty in the evaluation of percentile ranks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(11), pages 2349-2350, November.
  • Handle: RePEc:bla:jamist:v:63:y:2012:i:11:p:2349-2350
    DOI: 10.1002/asi.22714
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    Cited by:

    1. Schreiber, Michael, 2014. "How to improve the outcome of performance evaluations in terms of percentiles for citation frequencies of my papers," Journal of Informetrics, Elsevier, vol. 8(4), pages 873-879.
    2. Guoqiang Liang & Haiyan Hou & Qiao Chen & Zhigang Hu, 2020. "Diffusion and adoption: an explanatory model of “question mark” and “rising star” articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 219-232, July.
    3. Michael Schreiber, 2013. "How much do different ways of calculating percentiles influence the derived performance indicators? A case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 821-829, December.
    4. Bornmann, Lutz & Leydesdorff, Loet & Wang, Jian, 2013. "Which percentile-based approach should be preferred for calculating normalized citation impact values? An empirical comparison of five approaches including a newly developed citation-rank approach (P1," Journal of Informetrics, Elsevier, vol. 7(4), pages 933-944.
    5. Schreiber, Michael, 2014. "Is the new citation-rank approach P100′ in bibliometrics really new?," Journal of Informetrics, Elsevier, vol. 8(4), pages 997-1004.

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