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Estimating the accuracies of journal impact factor through bootstrap

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  • Chen, Kuan-Ming
  • Jen, Tsung-Hau
  • Wu, Margaret

Abstract

The journal impact factor (JIF) reported in journal citation reports has been used to represent the influence and prestige of a journal. Whereas the consideration of the stochastic nature of a statistic is a prerequisite for statistical inference, the estimation of JIF uncertainty is necessary yet unavailable for comparing the impact among journals. Using journals in the Database of Research in Science Education (DoRISE), the current study proposes bootstrap methods to estimate the JIF variability. The paper also provides a comprehensive exposition of the sources of JIF variability. The collections of articles in the year of interest and in the preceding years both contribute to JIF variability. In addition, the variability estimate differs depending on the way a database selects its journals for inclusion. In the bootstrap process, the nested structure of articles in a journal was accounted for to ensure that each bootstrap replication reflects the actual citation characteristics of articles in the journal. In conclusion, the proposed point and interval estimates of the JIF statistic are obtained and more informative inferences on the impact of journals can be drawn.

Suggested Citation

  • Chen, Kuan-Ming & Jen, Tsung-Hau & Wu, Margaret, 2014. "Estimating the accuracies of journal impact factor through bootstrap," Journal of Informetrics, Elsevier, vol. 8(1), pages 181-196.
    • Handle: RePEc:eee:infome:v:8:y:2014:i:1:p:181-196
    DOI: 10.1016/j.joi.2013.11.007
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    3. Cristiano Varin & Manuela Cattelan & David Firth, 2016. "Statistical modelling of citation exchange between statistics journals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(1), pages 1-63, January.

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