The generalized propensity score methodology for estimating unbiased journal impact factors

Rüdiger Mutz () and Hans-Dieter Daniel
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Rüdiger Mutz: ETH Zurich
Hans-Dieter Daniel: ETH Zurich

Scientometrics, 2012, vol. 92, issue 2, No 18, 377-390

Abstract: Abstract The journal impact factor (JIF) proposed by Garfield in the year 1955 is one of the most commonly used and prominent citation-based indicators of the performance and significance of a scientific journal. The JIF is simple, reasonable, clearly defined, and comparable over time and, what is more, can be easily calculated from data provided by Thomson Reuters, but at the expense of serious technical and methodological flaws. The paper discusses one of the core problems: The JIF is affected by bias factors (e.g., document type) that have nothing to do with the prestige or quality of a journal. For solving this problem, we suggest using the generalized propensity score methodology based on the Rubin Causal Model. Citation data for papers of all journals in the ISI subject category “Microscopy” (Journal Citation Report) are used to illustrate the proposal.

Keywords: Journal impact factor; Causal inference; Generalized propensity score; Rubin Causal Model (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (8)

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DOI: 10.1007/s11192-012-0670-4

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