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Modeling the probabilistic distribution of the impact factor

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  • Sarabia, José María
  • Prieto, Faustino
  • Trueba, Carmen

Abstract

The study of the informetric distributions, such as distributions of citations and impact factors is one of the most relevant topics in the current informetric research. Several laws for modeling impact factor based on ranks have been proposed, including Zipf, Lavalette and the two-exponent law proposed by Mansilla et al. (2007). In this paper, the underlying probabilistic quantile function corresponding to the Mansilla's two-exponent law is obtained. This result is particularly relevant, since it allows us to know the underlying population, to learn about all its features and to use statistical inference procedures. Several probabilistic descriptive measures are obtained, including moments, Lorenz and Leimkuhler curves and Gini index. The distribution of the order statistics is derived. Least squares estimates are obtained. The different results are illustrated using the data of the impact factors in eight relevant scientific fields.

Suggested Citation

  • Sarabia, José María & Prieto, Faustino & Trueba, Carmen, 2012. "Modeling the probabilistic distribution of the impact factor," Journal of Informetrics, Elsevier, vol. 6(1), pages 66-79.
    • Handle: RePEc:eee:infome:v:6:y:2012:i:1:p:66-79
    DOI: 10.1016/j.joi.2011.09.005
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    References listed on IDEAS

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    1. Sarabia, J. -M. & Castillo, Enrique & Slottje, Daniel J., 1999. "An ordered family of Lorenz curves," Journal of Econometrics, Elsevier, vol. 91(1), pages 43-60, July.
    2. Mansilla, R. & Köppen, E. & Cocho, G. & Miramontes, P., 2007. "On the behavior of journal impact factor rank-order distribution," Journal of Informetrics, Elsevier, vol. 1(2), pages 155-160.
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    13. Sarabia, José María & Gómez-Déniz, Emilio & Sarabia, María & Prieto, Faustino, 2010. "A general method for generating parametric Lorenz and Leimkuhler curves," Journal of Informetrics, Elsevier, vol. 4(4), pages 524-539.
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    2. Richard S.J. Tol, 2013. "Measuring catch-up growth in malnourished populations," Working Paper Series 6013, Department of Economics, University of Sussex Business School.
    3. Bertoli-Barsotti, Lucio & Lando, Tommaso, 2019. "How mean rank and mean size may determine the generalised Lorenz curve: With application to citation analysis," Journal of Informetrics, Elsevier, vol. 13(1), pages 387-396.
    4. Alina MOROSANU, 2013. "Empirical Study Of Different Factors Effects On Articles Publication Regarding Survey Interviewer Characteristics Using Multilevel Regression Model," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(1), pages 141-156, May.
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    6. Unnikrishnan Nair, N. & Vineshkumar, B., 2022. "Modelling informetric data using quantile functions," Journal of Informetrics, Elsevier, vol. 16(2).
    7. Mrowinski, Maciej J. & Gagolewski, Marek & Siudem, Grzegorz, 2022. "Accidentality in journal citation patterns," Journal of Informetrics, Elsevier, vol. 16(4).
    8. Brzezinski, Michal, 2014. "Empirical modeling of the impact factor distribution," Journal of Informetrics, Elsevier, vol. 8(2), pages 362-368.

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