Predictive aspects of a stochastic model for citation processes
Information Processing and Management: an International Journal
Journal of Mathematical Psychology
Predicting future citation behavior
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Comparing bibliometric statistics obtained from the Web of Science and Scopus
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Alternative thoughts on uncitedness
Journal of the American Society for Information Science and Technology
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Regression equations to predict h index trajectories up to 10 years ahead have been recently derived from the analysis of data from a large calibration sample of neuroscientists. These equations were regarded by their proponents as potentially useful decision aids for funding agencies, peer reviewers, and hiring committees. This paper presents the results of a validation study in a sample of Spanish psychologists including neuroscience psychologists for whom the regression equations would be expected to apply but including also psychologists in other areas of the social/behavioral sciences for whom the applicability of the regression equations might be questionable. The results do not support the equations for any of the two groups: Errors of prediction were generally large and mostly positive, the more so the larger was the value of the h index used to make the prediction. Although the validity of these regression equations could still be investigated in additional cross-validation studies, an alternative approach to predicting future h indices is outlined and illustrated in this paper.