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Uncertainties and ambiguities in percentiles and how to avoid them

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  • Michael Schreiber

Abstract

The recently proposed fractional scoring scheme is used to attribute publications to percentile rank classes. It is shown that in this way uncertainties and ambiguities in the evaluation of specific quantile values and percentile ranks do not occur. Using the fractional scoring the total score of all papers exactly reproduces the theoretical value.

Suggested Citation

  • Michael Schreiber, 2013. "Uncertainties and ambiguities in percentiles and how to avoid them," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(3), pages 640-643, March.
    • Handle: RePEc:bla:jamist:v:64:y:2013:i:3:p:640-643
    DOI: 10.1002/asi.22752
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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. 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.
    3. Schreiber, Michael, 2014. "Is the new citation-rank approach P100′ in bibliometrics really new?," Journal of Informetrics, Elsevier, vol. 8(4), pages 997-1004.
    4. Schreiber, Michael, 2014. "Examples for counterintuitive behavior of the new citation-rank indicator P100 for bibliometric evaluations," Journal of Informetrics, Elsevier, vol. 8(3), pages 738-748.
    5. Lutz Bornmann & Werner Marx & Andreas Barth, 2013. "The Normalization of Citation Counts Based on Classification Systems," Publications, MDPI, vol. 1(2), pages 1-9, August.

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