IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v179y2016i1p1-63.html
   My bibliography  Save this article

Statistical modelling of citation exchange between statistics journals

Author

Listed:
  • Cristiano Varin
  • Manuela Cattelan
  • David Firth

Abstract

type="main" xml:id="rssa12124-abs-0001"> Rankings of scholarly journals based on citation data are often met with scepticism by the scientific community. Part of the scepticism is due to disparity between the common perception of journals’ prestige and their ranking based on citation counts. A more serious concern is the inappropriate use of journal rankings to evaluate the scientific influence of researchers. The paper focuses on analysis of the table of cross-citations among a selection of statistics journals. Data are collected from the Web of Science database published by Thomson Reuters. Our results suggest that modelling the exchange of citations between journals is useful to highlight the most prestigious journals, but also that journal citation data are characterized by considerable heterogeneity, which needs to be properly summarized. Inferential conclusions require care to avoid potential overinterpretation of insignificant differences between journal ratings. Comparison with published ratings of institutions from the UK's research assessment exercise shows strong correlation at aggregate level between assessed research quality and journal citation ‘export scores’ within the discipline of statistics.

Suggested Citation

  • Cristiano Varin & Manuela Cattelan & David Firth, 2016. "Statistical modelling of citation exchange between statistics journals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(1), pages 1-63, January.
  • Handle: RePEc:bla:jorssa:v:179:y:2016:i:1:p:1-63
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/rssa.2016.179.issue-1
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
    2. Loet Leydesdorff & Filippo Radicchi & Lutz Bornmann & Claudio Castellano & Wouter Nooy, 2013. "Field-normalized impact factors (IFs): A comparison of rescaling and fractionally counted IFs," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(11), pages 2299-2309, November.
    3. Loet Leydesdorff & Tobias Opthof, 2010. "Scopus's source normalized impact per paper (SNIP) versus a journal impact factor based on fractional counting of citations," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(11), pages 2365-2369, November.
    4. Ignacio Palacios-Huerta & Oscar Volij, 2004. "The Measurement of Intellectual Influence," Econometrica, Econometric Society, vol. 72(3), pages 963-977, May.
    5. Klaus Ritzberger, 2008. "A Ranking of Journals in Economics and Related Fields," German Economic Review, Verein für Socialpolitik, vol. 9, pages 402-430, November.
    6. Mark E. Glickman, 1999. "Parameter Estimation in Large Dynamic Paired Comparison Experiments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(3), pages 377-394.
    7. Turner, Heather & Firth, David, 2012. "Bradley-Terry Models in R: The BradleyTerry2 Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i09).
    8. Fionn Murtagh & Michael J. Kurtz, 2016. "The Classification Society’s Bibliography Over Four Decades: History and Content Analysis," Journal of Classification, Springer;The Classification Society, vol. 33(1), pages 6-29, April.
    9. Bien, Jacob & Tibshirani, Robert, 2011. "Hierarchical Clustering With Prototypes via Minimax Linkage," Journal of the American Statistical Association, American Statistical Association, vol. 106(495), pages 1075-1084.
    10. Frandsen, Tove Faber, 2007. "Journal self-citations—Analysing the JIF mechanism," Journal of Informetrics, Elsevier, vol. 1(1), pages 47-58.
    11. Loet Leydesdorff & Lutz Bornmann, 2011. "How fractional counting of citations affects the impact factor: Normalization in terms of differences in citation potentials among fields of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(2), pages 217-229, February.
    12. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    13. Waltman, Ludo & van Eck, Nees Jan & van Leeuwen, Thed N. & Visser, Martijn S., 2013. "Some modifications to the SNIP journal impact indicator," Journal of Informetrics, Elsevier, vol. 7(2), pages 272-285.
    14. Gaines Liner & Minesh Amin, 2004. "Methods of ranking economics journals," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 32(2), pages 140-149, June.
    15. Ting Yan & Jinfeng Xu, 2013. "A central limit theorem in the β-model for undirected random graphs with a diverging number of vertices," Biometrika, Biometrika Trust, vol. 100(2), pages 519-524.
    16. Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
    17. Francesco Bartolucci & Valentino Dardanoni & Franco Peracchi, 2015. "Ranking scientific journals via latent class models for polytomous item response data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 1025-1049, October.
    18. Robert Tibshirani & Michael Saunders & Saharon Rosset & Ji Zhu & Keith Knight, 2005. "Sparsity and smoothness via the fused lasso," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(1), pages 91-108, February.
    19. Krivitsky, Pavel N. & Handcock, Mark S., 2008. "Fitting Latent Cluster Models for Networks with latentnet," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i05).
    20. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
    21. Chen, Kuan-Ming & Jen, Tsung-Hau & Wu, Margaret, 2014. "Estimating the accuracies of journal impact factor through bootstrap," Journal of Informetrics, Elsevier, vol. 8(1), pages 181-196.
    22. Manuela Cattelan & Cristiano Varin & David Firth, 2013. "Dynamic Bradley–Terry modelling of sports tournaments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(1), pages 135-150, January.
    23. Erjen Van Nierop, 2009. "Why do statistics journals have low impact factors?," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(1), pages 52-62, February.
    24. Stigler, George J & Stigler, Stephen M & Friedland, Claire, 1995. "The Journals of Economics," Journal of Political Economy, University of Chicago Press, vol. 103(2), pages 331-359, April.
    25. Zheng Tracy Ke & Jianqing Fan & Yichao Wu, 2015. "Homogeneity Pursuit," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 175-194, March.
    26. Manuela Cattelan & Cristiano Varin, 2013. "Hybrid Pairwise Likelihood Analysis of Animal Behavior Experiments," Biometrics, The International Biometric Society, vol. 69(4), pages 1002-1011, December.
    27. Bornmann, Lutz, 2014. "Do altmetrics point to the broader impact of research? An overview of benefits and disadvantages of altmetrics," Journal of Informetrics, Elsevier, vol. 8(4), pages 895-903.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sebastian Szugat & Ivan Bakhtin & Leo Fechtel & Marc Hüsch & Julian Riehl & Carsten Tegethoff & Christine H. Müller, 2017. "Bedingungen für hohe Publikationsraten von Ländern in hochrangigen internationalen Statistik-Fachzeitschriften [Conditions for high publication rates of countries in high-ranking international stat," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 11(1), pages 33-49, April.
    2. Ke, Qing, 2018. "Comparing scientific and technological impact of biomedical research," Journal of Informetrics, Elsevier, vol. 12(3), pages 706-717.
    3. Arne Risa Hole, 2017. "Ranking Economics Journals Using Data From a National Research Evaluation Exercise," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 621-636, October.
    4. Ryan P Womack, 2015. "Research Data in Core Journals in Biology, Chemistry, Mathematics, and Physics," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-22, December.
    5. Battistin, Erich & Ovidi, Marco, 2017. "Rising Stars," CEPR Discussion Papers 12488, C.E.P.R. Discussion Papers.
    6. Francesca Giambona & Mariano Porcu & Isabella Sulis, 2017. "Students Mobility: Assessing the Determinants of Attractiveness Across Competing Territorial Areas," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(3), pages 1105-1132, September.
    7. François Caron & Emily B. Fox, 2017. "Sparse graphs using exchangeable random measures," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1295-1366, November.
    8. Yurij L. Katchanov & Yulia V. Markova, 2017. "The “space of physics journals”: topological structure and the Journal Impact Factor," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 313-333, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jorssa:v:179:y:2016:i:1:p:1-63. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley Content Delivery). General contact details of provider: http://edirc.repec.org/data/rssssea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.