Scoring research output using statistical quantile plotting

Jan Beirlant, W. Glänzel, An Carbonez, Herlinde Leemans

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

In this paper, we propose two methods for scoring scientific output based on statistical quantile plotting. First, a rescaling of journal impact factors for scoring scientific output on a macro level is proposed. It is based on normal quantile plotting which allows to transform impact data over several subject categories to a standardized distribution. This can be used in comparing scientific output of larger entities such as departments working in quite different areas of research. Next, as an alternative to the Hirsch index [Hirsch, J.E. (2005). An index to quantify an individuals scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569-16572], the extreme value index is proposed as an indicator for assessment of the research performance of individual scientists. In case of Lotkaian-Zipf-Pareto behaviour of citation counts of an individual, the extreme value index can be interpreted as the slope in a Pareto-Zipf quantile plot. This index, in contrast to the Hirsch index, is not influenced by the number of publications but stresses the decay of the statistical tail of citation counts. It appears to be much less sensitive to the science field than the Hirsch index.

Original languageEnglish
Pages (from-to)185-192
Number of pages8
JournalJournal of Informetrics
Volume1
Issue number3
DOIs
Publication statusPublished - Jul 2007

Fingerprint

Quantile
Scoring
Hirsch Index
Extreme Value Index
Output
Citations
Pareto
Count
Impact Factor
Macros
Rescaling
Tail
Slope
Quantify
Decay
Transform
Academy of Sciences
macro level
Research output
Alternatives

Keywords

  • Extreme value index
  • Normal quantile plot
  • Pareto quantile plot
  • Quantile plots
  • Standardizing

ASJC Scopus subject areas

  • Applied Mathematics
  • Modelling and Simulation
  • Statistics and Probability
  • Management Science and Operations Research
  • Computer Science Applications

Cite this

Scoring research output using statistical quantile plotting. / Beirlant, Jan; Glänzel, W.; Carbonez, An; Leemans, Herlinde.

In: Journal of Informetrics, Vol. 1, No. 3, 07.2007, p. 185-192.

Research output: Contribution to journalArticle

Beirlant, Jan ; Glänzel, W. ; Carbonez, An ; Leemans, Herlinde. / Scoring research output using statistical quantile plotting. In: Journal of Informetrics. 2007 ; Vol. 1, No. 3. pp. 185-192.
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