Open AccessBig Macs and Eigenfactor scores: Don't let correlation coefficients fool you
Author(s) -
West Jevin,
Bergstrom Theodore,
Bergstrom Carl T.
Publication year - 2010
Publication title -
journal of the american society for information science and technology
Language(s) - English
Resource type - Journals
eISSN - 1532-2890
pISSN - 1532-2882
DOI - 10.1002/asi.21374
Subject(s) - correlation , statistics , mathematics , computer science , geometry
The Eigenfactor™ Metrics provide an alternative way of evaluating scholarly journals based on an iterative ranking procedure analogous to Google's PageRank algorithm. These metrics have recently been adopted by Thomson Reuters and are listed alongside the Impact Factor in the Journal Citation Reports . But do these metrics differ sufficiently so as to be a useful addition to the bibliometric toolbox? Davis (2008) has argued that they do not, based on his finding of a 0.95 correlation coefficient between Eigenfactor score and Total Citations for a sample of journals in the field of medicine. This conclusion is mistaken; in this article, we illustrate the basic statistical fallacy to which Davis succumbed. We provide a complete analysis of the 2006 Journal Citation Reports and demonstrate that there are statistically and economically significant differences between the information provided by the Eigenfactor Metrics and that provided by Impact Factor and Total Citations.