How to consider fractional counting and field normalization in the statistical modeling of bibliometric data: A multilevel Poisson regression approach |
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| Authors: | Rüdiger Mutz Hans-Dieter Daniel |
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| Institution: | 1. Professorship for Social Psychology and Research on Higher Education, ETH Zurich, Zurich, Switzerland;2. Department of Psychology, University of Zurich, Switzerland |
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| Abstract: | The numerical-algorithmic procedures of fractional counting and field normalization are often mentioned as indispensable requirements for bibliometric analyses. Against the background of the increasing importance of statistics in bibliometrics, a multilevel Poisson regression model (level 1: publication, level 2: author) shows possible ways to consider fractional counting and field normalization in a statistical model (fractional counting I). However, due to the assumption of duplicate publications in the data set, the approach is not quite optimal. Therefore, a more advanced approach, a multilevel multiple membership model, is proposed that no longer provides for duplicates (fractional counting II). It is assumed that the citation impact can essentially be attributed to time-stable dispositions of researchers as authors who contribute with different fractions to the success of a publication’s citation. The two approaches are applied to bibliometric data for 254 scientists working in social science methodology. A major advantage of fractional counting II is that the results no longer depend on the type of fractional counting (e.g., equal weighting). Differences between authors in rankings are reproduced more clearly than on the basis of percentiles. In addition, the strong importance of field normalization is demonstrated; 60% of the citation variance is explained by field normalization. |
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| Keywords: | Corresponding author at: Professorship for Social Psychology and Research on Higher Education ETH Zurich Andreasstrasse 15 8050 Zurich Switzerland Fractional counting Field normalization Multilevel model Poisson regression Multilevel multiple membership model |
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