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The Rasch model. Measuring the impact of scientific journals: Analytical chemistry

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  • Pedro Alvarez
  • Antonio Pulgarín

Abstract

This article focuses on a fresh way to determine a ranking of science journals according to the “number of citations‐to and items‐published,” data used by SCI JCR of ISI to determine journal ranking by “impact factor.” This is the first application of latent traits theory to bibliometrics. “Impact” is considered a latent variable defined by a set of items (or indicators), citations, and sources. The theoretical background is Item Response Theory, which suggests that, if we can understand how each item in a set of items operates with an object, then we can estimate a measure for the object. The Rasch model is the commonest formulation of that theory. This technique is here applied to the citations and sources of 43 Analytical Chemistry journals (objects) to provide a Rasch measure for these journals which is compared with the current “impact factor” computation. © 1996 John Wiley & Sons, Inc.

Suggested Citation

  • Pedro Alvarez & Antonio Pulgarín, 1996. "The Rasch model. Measuring the impact of scientific journals: Analytical chemistry," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 47(6), pages 458-467, June.
    • Handle: RePEc:bla:jamest:v:47:y:1996:i:6:p:458-467
    DOI: 10.1002/(SICI)1097-4571(199606)47:63.0.CO;2-U
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    Cited by:

    1. Shakil Ahmad & Yasir Javed & Shabir Hussain Khahro & Arslan Shahid, 2020. "Research Contribution of the Oldest Seat of Higher Learning in Pakistan: A Bibliometric Analysis of University of the Punjab," Publications, MDPI, vol. 8(3), pages 1-15, September.
    2. Boris Forthmann, 2023. "Researcher capacity estimation based on the Q model: a generalized linear mixed model perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4753-4764, August.
    3. Sorensen, Jon R., 2009. "An assessment of the relative impact of criminal justice and criminology journals," Journal of Criminal Justice, Elsevier, vol. 37(5), pages 505-511, September.
    4. Mutz, Rüdiger & Daniel, Hans-Dieter, 2018. "The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model," Journal of Informetrics, Elsevier, vol. 12(4), pages 1282-1295.
    5. Wolfgang Glänzel & Henk F. Moed, 2013. "Opinion paper: thoughts and facts on bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 381-394, July.

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