Advanced Search
MyIDEAS: Login

Ranking Scientific Journals via Latent Class Models for Polytomous Item Response

Contents:

Author Info

  • 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.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
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

Bibliographic Info

Paper provided by Einaudi Institute for Economics and Finance (EIEF) in its series EIEF Working Papers Series with number 1313.

as in new window
Length: 26 pages
Date of creation: 2013
Date of revision: May 2013
Handle: RePEc:eie:wpaper:1313

Contact details of provider:
Postal: Via Sallustiana, 62 - 00187 Roma
Phone: +39 066790013
Fax: +39 0647924872
Email:
Web page: http://www.eief.it/repec
More information through EDIRC

Related research

Keywords:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Chia-Lin Chang & Michael McAleer & Les Oxley, 2010. "Journal Impact Factor Versus Eigenfactor and Article Influence," Working Papers in Economics 10/67, University of Canterbury, Department of Economics and Finance.
  2. Christian Zimmermann, 2007. "Academic Rankings with RePEc," Working papers 2007-36, University of Connecticut, Department of Economics, revised Mar 2009.
  3. Francesco Bartolucci, 2007. "A class of multidimensional IRT models for testing unidimensionality and clustering items," Psychometrika, Springer, vol. 72(2), pages 141-157, June.
  4. 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.
Full references (including those not matched with items on IDEAS)

Citations

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography for Economics:
  1. > Economics Profession > Ranking in Economics > Ranking Methodology
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Bertocchi, Graziella & Gambardella, Alfonso & Jappelli, Tullio & Nappi, Carmela A. & Peracchi, Franco, 2013. "Bibliometric Evaluation vs. Informed Peer Review: Evidence from Italy," CEPR Discussion Papers 9724, C.E.P.R. Discussion Papers.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

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).

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.