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Statistical modelling of citation exchange between statistics journals

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  • 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.

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  • 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
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    1. 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.
    2. 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.
    3. 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).
    4. 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.
    5. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
    6. Theoharakis V. & Skordia M., 2003. "How Do Statisticians Perceive Statistics Journals?," The American Statistician, American Statistical Association, vol. 57, pages 115-123, May.
    7. Nowicki K. & Snijders T. A. B., 2001. "Estimation and Prediction for Stochastic Blockstructures," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1077-1087, September.
    8. Richard Van Noorden & Brendan Maher & Regina Nuzzo, 2014. "The top 100 papers," Nature, Nature, vol. 514(7524), pages 550-553, October.
    9. 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.
    10. 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 Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(2), pages 217-229, February.
    11. Donald O. Case & Georgeann M. Higgins, 2000. "How can we investigate citation behavior? A study of reasons for citing literature in communication," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(7), pages 635-645.
    12. Kevin W. Boyack & Richard Klavans & Katy Börner, 2005. "Mapping the backbone of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(3), pages 351-374, August.
    13. Ignacio Palacios-Huerta & Oscar Volij, 2004. "The Measurement of Intellectual Influence," Econometrica, Econometric Society, vol. 72(3), pages 963-977, May.
    14. repec:bla:germec:v:9:y:2008:i::p:402-430 is not listed on IDEAS
    15. 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.
    16. 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.
    17. 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).
    18. Wolfgang Glänzel & Henk F. Moed, 2002. "Journal impact measures in bibliometric research," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(2), pages 171-193, February.
    19. Diana Hicks & Paul Wouters & Ludo Waltman & Sarah de Rijcke & Ismael Rafols, 2015. "Bibliometrics: The Leiden Manifesto for research metrics," Nature, Nature, vol. 520(7548), pages 429-431, April.
    20. 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.
    21. 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.
    22. Richard Van Noorden, 2013. "Brazilian citation scheme outed," Nature, Nature, vol. 500(7464), pages 510-511, August.
    23. Gelman A. & Pasarica C. & Dodhia R., 2002. "Lets Practice What We Preach: Turning Tables into Graphs," The American Statistician, American Statistical Association, vol. 56, pages 121-130, May.
    24. 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.
    25. Hoff P.D. & Raftery A.E. & Handcock M.S., 2002. "Latent Space Approaches to Social Network Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1090-1098, December.
    26. 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.
    27. Harvey Goldstein & David J. Spiegelhalter, 1996. "League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(3), pages 385-409, May.
    28. 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.
    29. Pablo D. Batista & Mônica G. Campiteli & Osame Kinouchi, 2006. "Is it possible to compare researchers with different scientific interests?," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(1), pages 179-189, July.
    30. Frandsen, Tove Faber, 2007. "Journal self-citations—Analysing the JIF mechanism," Journal of Informetrics, Elsevier, vol. 1(1), pages 47-58.
    31. David Colquhoun, 2003. "Challenging the tyranny of impact factors," Nature, Nature, vol. 423(6939), pages 479-479, May.
    32. Loet Leydesdorff & Jung C. Shin, 2011. "How to evaluate universities in terms of their relative citation impacts: Fractional counting of citations and the normalization of differences among disciplines," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(6), pages 1146-1155, June.
    33. Luca Pratelli & Alberto Baccini & Lucio Barabesi & Marzia Marcheselli, 2012. "Statistical Analysis of the Hirsch Index," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 39(4), pages 681-694, December.
    34. 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.
    35. 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.
    36. 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.
    37. Lutz Bornmann & Werner Marx, 2014. "How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 487-509, January.
    38. Michel Zitt & Henry Small, 2008. "Modifying the journal impact factor by fractional citation weighting: The audience factor," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(11), pages 1856-1860, September.
    39. 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.
    40. 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.
    41. Ritzberger Klaus, 2008. "A Ranking of Journals in Economics and Related Fields," German Economic Review, De Gruyter, vol. 9(4), pages 402-430, December.
    42. 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.
    43. 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.
    44. Ludo Waltman & Nees Jan Eck, 2013. "Source normalized indicators of citation impact: an overview of different approaches and an empirical comparison," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 699-716, September.
    45. 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.
    46. 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.
    47. Mark P. Carpenter & Francis Narin, 1973. "Clustering of scientific journals," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(6), pages 425-436, November.
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