Skip to main content
SpringerLink
Log in

Application of the Rasch model to measuring the impact of scientific journals

  • Published:
Publishing Research Quarterly Aims and scope

Abstract

This paper focuses on a fresh and fair way to determine a ranking of science journals according to the “number of citations-to and articles published,” data used by SCI Journal Citation Reports of ISI to determine journal ranking by “impact factor.” Impact is considered a latent variable defined by a set of items (citations and articles published). 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 most common formulation of that theory. This technique is here applied to the citations and articles published of 62 medical journals (objects) to provide a Rasch measure for these journals which is compared with the current “impact factor” computation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Andrich, D. 1988.Rasch model for measurement. Murdoch University, Australia: Sage.

  • Asai, I. 1981. Adjusted age distribution and its application to impact factor and immediacy index.Journal of the American Society for Information Science 32(3): 172–174.

    Article  Google Scholar 

  • Bookstein, A. 1976. The bibliometric distributions.Library Quarterly 46(4): 416–423.

    Google Scholar 

  • Bradford, S. C. 1934. Sources of information on specific subjects.Engineering 137: 85–86.

    Google Scholar 

  • Bradford, S. C. 1948.Documentation. London, England: Crosby Lockwood and Sons.

    Google Scholar 

  • Brookes, B. C. 1973. Numerical methods of bibliographic analysis.Library Trends 22(1): 18–43.

    Google Scholar 

  • Cole, F. J., and Eales, N. B. 1917. The history of comparative anatomy.Science Progress 11: 578–596.

    Google Scholar 

  • Collins, H.M. 1982.Tactic knowledge and scientific networks. In B. B. a. D. Edge (Ed.),Science in Context: Readings in the Sociology of Knowledge. Cambridge: MIT Press.

    Google Scholar 

  • Coombs, C. H. 1964.A theory of data. New York: Wiley.

    Google Scholar 

  • Cronin, B. 1984.The citation process. The role and significance of citation in scientific communication. London: Taylor Graham.

    Google Scholar 

  • Duran, D. E. 1974. A citation count analysis of behavioral science journals in influential management literature.Academy of Management Journal 17: 579–583.

    Article  Google Scholar 

  • Egghe, L. 1988. Mathematical relations between impact factors and average number of citations.Information Processing and Management 24(5): 567–576.

    Article  Google Scholar 

  • Elkana, Y., Lederberg, J., Merton, R. K., Thackery, A., and Zuckerman, H. 1978.Toward a metric of science. The advent of science indicators. New York: John Wiley Sons.

    Google Scholar 

  • Everett, J. E., and Pecotich, A. 1991. A combined logniear/MDS model for mapping journals by citation analysis.Journal of the American Society for Information Science 42(6): 405–413.

    Article  Google Scholar 

  • Fussler, H. H. 1949. Characteristics of the research literature used by chemists and physicists in the United States. Part II.Library Quarterly 19(2): 119–143.

    Article  Google Scholar 

  • Garfield, E. 1972. Citation analysis as a tool in journal evaluation.Science 178(4060): 471–479.

    Article  Google Scholar 

  • Garfield, E. 1979. Is citation analysis a legitimate evaluation tool?.Scientometrics 1(4): 359–375.

    Article  Google Scholar 

  • Garfield, Eugene (Ed.). 1993. SCI Journal Citation Reports. Philadelphia, PA: Institute for Scientific Information.

    Google Scholar 

  • Gilbert, G. N. 1978. Measuring the growth of science: a review of indicators of scientific growth.Scientometrics 1 (1): 9–34.

    Article  Google Scholar 

  • Goldman, A. 1979. Publishing activity in marketing as an indicator of its structure and disciplinary boundaries.Journal of Marketing Research XVI: 485–494.

    Article  Google Scholar 

  • Gross, P. L. K., and Gross, E. M. 1927. College libraries and chemical education.Science 66: 1229–1234.

    Google Scholar 

  • Hamelman, P. W. and Mazze, E. M. 1973. Cross-referencing between AMA journals and other publications.Journal of Marketing Research X: 215–218.

    Article  Google Scholar 

  • Hjerppe, R. 1980.A bibliography of bibliometrics and citation indexing and analysis (No. TRITA-LIB-2913). Stockholm papers in Library and Information Science. The Royal Institute of Technology.

  • Hulme, E. W. 1923.Statistical bibliography in relation to the growth of modern civilization. London, England: Grafton.

    Google Scholar 

  • Kendall, M. G. 1960. the bibliography of operational research.Operational Research Quarterly 11(1/2): 31–36.

    Article  Google Scholar 

  • King, J. A. 1987. A review of bibliometric and other science indicators and their role in research evaluation.Journal of Information Science. Principles and Practice 13(5): 261–276.

    Google Scholar 

  • Koenig, E. D. 1983. Bibliometric indicators versus expert opinion in assessing research performance.Journal of the American Society for Information Science 34(2): 136–145.

    Article  Google Scholar 

  • MacRoberts, M. H., and MacRoberts, B. R. 1989. Problems of citation analysis. A critical review.Journal of the American Society for Information Science 40(5): 342–349.

    Article  Google Scholar 

  • Moed, H. F., Burguer, W. J. M., Frankfort, J. G., and van Raan, A. A. J. 1983.On the measurement of research performance. The use of bibliometric indicators. Research Policy Unit. Diensten OWZ/PISA. State University of Leiden. Leiden. The Netherlands.

    Google Scholar 

  • Narin, F. 1976.Evaluative bibliometrics: The use of publication and citation analysis in the evaluation of scientific activity (No. PB-252339). Cherry Hill, NJ: Computer Horizons, Inc. National Science Foundation.

    Google Scholar 

  • Narin, F., and Moll, J. K. 1977. Bibliometrics.Annual Review of Information Science and Technology 12: 35–58.

    Google Scholar 

  • Porter, A., Chubin, D. E., and Jin, X. 1988. Citations and scientific progress. Comparing bibliometric measures with scientific judgments.Scientometrics 13(3–4): 103–124.

    Article  Google Scholar 

  • Price, D. de S. 1963.Little science, big science. New York: Columbia University Press.

    Google Scholar 

  • Price, D. de S. 1976. A general theory of bibliometric and other cumulative advantage processes.Journal of the American Society for Information Science 27(5): 292–306.

    Article  Google Scholar 

  • Rasch, G. 1980.Probabilistic models for some intelligence and attainment tests. Chicago: The University of Chicago Press.

    Google Scholar 

  • Sen, B. K. 1992. Documentation note. Normalised impact factor.Journal of Documentation 48(3): 318–325.

    Google Scholar 

  • Sen, B. K., Karanjai, A., and Munshi, V. M. 1989. A method for determining the impact factor of a non-SCI journal.Journal of Documentation 45(2): 139–141.

    Google Scholar 

  • Simon, H. A. 1955. On a class of skew distribution functions.Biometrika 42: 425–440.

    Google Scholar 

  • Todorov, R., and Glanzel, W. 1988. Journal citation measures: A concise review.Journal of Information Science 14: 47–56.

    Article  Google Scholar 

  • Van Raan, A. F. J., and Hartmann, D. 1987. The comparative impact of scientific publications and journals: methods of measurement and graphical display.Scientometrics 11(5–6): 325–331.

    Article  Google Scholar 

  • Vocino, T., and Elliott, R. H. 1984. Research note: Public administration journal prestige: A time series analysis.Administrative Science Quarterly 29: 43–51.

    Article  Google Scholar 

  • Weber, R. P., and Stevenson, A. 1981. Evaluation of accounting journals and department quality.Accounting Review 56: 596–612.

    Google Scholar 

  • Weinstock, M. 1971. Citation Indexes.Encyclopaedia of Library and Information Science 5: 16–40.

    Google Scholar 

  • Wright, B. D., and Stone, M. H. 1978.Best test design. Chicago: MESA Press.

    Google Scholar 

  • Zipf, G. K. 1949.Human behavior and the principle of least effort. Cambridge: Cambridge Mass.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Extremadura, Avd. Elvas s/n, 06071, Badajoz, Spain

    Pedro Alvarez & Antonio Pulgarín

Authors
  1. Pedro Alvarez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Antonio Pulgarín
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Alvarez, P., Pulgarín, A. Application of the Rasch model to measuring the impact of scientific journals. Publishing Research Quarterly 12, 57–64 (1996). https://doi.org/10.1007/BF02680575

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02680575

Keywords

Search

Navigation