Big Macs and Eigenfactor Scores: Don't Let Correlation Coefficients Fool You

Details Big Macs and Eigenfactor Scores: Don't Let Correlation Coefficients Fool You Big Macs and Eigenfactor Scores: Don't Let Correlation Coefficients Fool You

2009-11-10

arxiv.org/abs/0911.1807v2

Computer Science

Digital Libraries

Version 2 This is a response to Phil Davis's 2008 paper (arXiv:0807.2678)

Scientific paper

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 otherwise, 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; here 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.

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