[scisip] McCall's Area Transformation versus the Integrated Impact Indicator (I3)
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In a study entitled "Skewed Citation Distributions and Bias Factors: Solutions to two core problems with the journal impact factor," Mutz & Daniel (2012) propose (i) McCall's (1922) Area Transformation of the skewed citation distribution so that this data can be considered as normally distributed (Krus & Kennedy, 1977), and (ii) to control for different document types as a co-variate (Rubin, 1977). This approach provides an alternative to Leydesdorff & Bornmann's (2011) Integrated Impact Indicator (I3). As the authors note, the two approaches are akin.
Can something be said about the relative quality of the two approaches? To that end, I replicated the study of Mutz & Daniel for the 11 journals in the Subject Category "mathematical psychology," but using additionally I3 on the basis of continuous quantiles (Leydesdorff & Bornmann, in press) and its variant PR6 based on the six percentile rank classes distinguished by Bornmann & Mutz (2011) as follows: the top-1%, 95-99%, 90-95%, 75-90%, 50-75%, and bottom-50%.
** apologies for cross-postings
Professor, University of AmsterdamAmsterdam School of Communications Research (ASCoR)Kloveniersburgwal 48, 1012 CX Amsterdam.Tel. +31-20-525 6598; fax: +31-842239111
email@example.com ; http://www.leydesdorff.net/ Visiting Professor, ISTIC, Beijing; Honorary Fellow, SPRU, University of Sussex; http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en
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