IDEAS home Printed from https://ideas.repec.org/p/eie/wpaper/1313.html
   My bibliography  Save this paper

Ranking Scientific Journals via Latent Class Models for Polytomous Item Response

Author

Listed:
  • Francesco Bartolucci

    (University of Perugia)

  • Valentino Dardanoni

    (University of Palermo)

  • Franco Peracchi

    (University of Rome "Tor Vergata" and EIEF)

Abstract

We propose a strategy for ranking scientific journals starting from a set of available quantitative indicators that represent imperfect measures of the unobservable "value" of the journals of interest. After discretizing the available indicators, we estimate a latent class model for polytomous item response data and use the estimated model to classify each journal. We apply the proposed approach to data from the Research Evaluation Exercise (VQR) carried out in Italy with reference to the period 2004-2010, focusing on the sub-area consisting of Statistics and Financial Mathematics. Using four quantitative indicators of the journals' scientific value (IF, IF5, AIS, h-index), some of which not available for all journals, we derive a complete ordering of the journals according to their latent value. We show that the proposed methodology is relatively simple to implement, even when the aim is to classify journals into finite ordered groups of a fixed size. Finally, we analyze the robustness of the obtained ranking with respect to different discretization rules.

Suggested Citation

  • Francesco Bartolucci & Valentino Dardanoni & Franco Peracchi, 2013. "Ranking Scientific Journals via Latent Class Models for Polytomous Item Response," EIEF Working Papers Series 1313, Einaudi Institute for Economics and Finance (EIEF), revised May 2013.
  • Handle: RePEc:eie:wpaper:1313
    as

    Download full text from publisher

    File URL: http://www.eief.it/files/2013/05/wp-13-ranking-scientific-journals-via-latent-class-models-for-polytomous-item-response-data.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Christian Zimmermann, 2013. "Academic Rankings with RePEc," Econometrics, MDPI, Open Access Journal, vol. 1(3), pages 1-32, December.
    2. Bartolucci, Francesco & Bacci, Silvia & Gnaldi, Michela, 2014. "MultiLCIRT: An R package for multidimensional latent class item response models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 971-985.
    3. Chang, C-L. & McAleer, M.J. & Oxley, L., 2010. "Journal Impect Factor Versus Eigenfactor and Article Influence," Econometric Institute Research Papers EI 2010-67, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Francesco Bartolucci, 2007. "A class of multidimensional IRT models for testing unidimensionality and clustering items," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 141-157, June.
    5. Althouse, Benjamin M. & West, Jevin D. & Bergstrom, Ted C & Bergstrom, Carl T., 2008. "Differences in Impact Factor Across Fields and Over Time," University of California at Santa Barbara, Economics Working Paper Series qt76h442pg, Department of Economics, UC Santa Barbara.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations

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


    Cited by:

    1. Bertocchi, Graziella & Gambardella, Alfonso & Jappelli, Tullio & Nappi, Carmela A. & Peracchi, Franco, 2015. "Bibliometric evaluation vs. informed peer review: Evidence from Italy," Research Policy, Elsevier, vol. 44(2), pages 451-466.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:eie:wpaper:1313. 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: (Facundo Piguillem). General contact details of provider: http://edirc.repec.org/data/einauit.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.