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Interrater reliability and convergent validity of F1000Prime peer review

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  • Lutz Bornmann

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  • Lutz Bornmann, 2015. "Interrater reliability and convergent validity of F1000Prime peer review," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(12), pages 2415-2426, December.
    • Handle: RePEc:bla:jinfst:v:66:y:2015:i:12:p:2415-2426
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    References listed on IDEAS

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    1. Ludo Waltman & Rodrigo Costas, 2014. "F1000 Recommendations as a Potential New Data Source for Research Evaluation: A Comparison With Citations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(3), pages 433-445, March.
    2. Bornmann, Lutz & Williams, Richard, 2013. "How to calculate the practical significance of citation impact differences? An empirical example from evaluative institutional bibliometrics using adjusted predictions and marginal effects," Journal of Informetrics, Elsevier, vol. 7(2), pages 562-574.
    3. James W. Hardin & Joseph W. Hilbe, 2012. "Generalized Linear Models and Extensions, 3rd Edition," Stata Press books, StataCorp LP, edition 3, number glmext, March.
    4. L. Iorio, 2014. "Withdrawal: ‘A new type of misconduct in the field of the physical sciences: The case of the pseudonyms used by I. Ciufolini to anonymously criticize other people's works on arXiv’ by L. Iorio," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(11), pages 2375-2375, November.
    5. Martin, Ben R. & Irvine, John, 1993. "Assessing basic research : Some partial indicators of scientific progress in radio astronomy," Research Policy, Elsevier, vol. 22(2), pages 106-106, April.
    6. Michael E. Reichenheim, 2004. "Confidence intervals for the kappa statistic," Stata Journal, StataCorp LP, vol. 4(4), pages 421-428, December.
    7. Bornmann, Lutz & Leydesdorff, Loet, 2013. "The validation of (advanced) bibliometric indicators through peer assessments: A comparative study using data from InCites and F1000," Journal of Informetrics, Elsevier, vol. 7(2), pages 286-291.
    8. Ehsan Mohammadi & Mike Thelwall, 2013. "Assessing non-standard article impact using F1000 labels," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 383-395, November.
    9. William H. Starbuck, 2005. "How Much Better Are the Most-Prestigious Journals? The Statistics of Academic Publication," Organization Science, INFORMS, vol. 16(2), pages 180-200, April.
    10. Bornmann, Lutz & Leydesdorff, Loet & Mutz, Rüdiger, 2013. "The use of percentiles and percentile rank classes in the analysis of bibliometric data: Opportunities and limits," Journal of Informetrics, Elsevier, vol. 7(1), pages 158-165.
    11. Benda, Wim G.G. & Engels, Tim C.E., 2011. "The predictive validity of peer review: A selective review of the judgmental forecasting qualities of peers, and implications for innovation in science," International Journal of Forecasting, Elsevier, vol. 27(1), pages 166-182.
    12. George A. Lozano & Vincent Larivière & Yves Gingras, 2012. "The weakening relationship between the impact factor and papers' citations in the digital age," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2140-2145, November.
    13. Benda, Wim G.G. & Engels, Tim C.E., 2011. "The predictive validity of peer review: A selective review of the judgmental forecasting qualities of peers, and implications for innovation in science," International Journal of Forecasting, Elsevier, vol. 27(1), pages 166-182, January.
    14. Rüdiger Mutz & Lutz Bornmann & Hans-Dieter Daniel, 2012. "Heterogeneity of Inter-Rater Reliabilities of Grant Peer Reviews and Its Determinants: A General Estimating Equations Approach," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-10, October.
    15. Michael N. Mitchell, 2012. "Interpreting and Visualizing Regression Models Using Stata," Stata Press books, StataCorp LP, number ivrm, March.
    16. Waltman, Ludo & van Eck, Nees Jan & van Leeuwen, Thed N. & Visser, Martijn S., 2013. "Some modifications to the SNIP journal impact indicator," Journal of Informetrics, Elsevier, vol. 7(2), pages 272-285.
    17. Lutz Bornmann & Rüdiger Mutz & Werner Marx & Hermann Schier & Hans‐Dieter Daniel, 2011. "A multilevel modelling approach to investigating the predictive validity of editorial decisions: do the editors of a high profile journal select manuscripts that are highly cited after publication?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(4), pages 857-879, October.
    18. Ludo Waltman & Clara Calero-Medina & Joost Kosten & Ed C.M. Noyons & Robert J.W. Tijssen & Nees Jan Eck & Thed N. Leeuwen & Anthony F.J. Raan & Martijn S. Visser & Paul Wouters, 2012. "The Leiden ranking 2011/2012: Data collection, indicators, and interpretation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2419-2432, December.
    19. Richard Williams, 2012. "Using the margins command to estimate and interpret adjusted predictions and marginal effects," Stata Journal, StataCorp LP, vol. 12(2), pages 308-331, June.
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    Cited by:

    1. Bornmann, Lutz & Leydesdorff, Loet, 2015. "Does quality and content matter for citedness? A comparison with para-textual factors and over time," Journal of Informetrics, Elsevier, vol. 9(3), pages 419-429.
    2. Robin Haunschild & Lutz Bornmann, 2018. "Field- and time-normalization of data with many zeros: an empirical analysis using citation and Twitter data," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 997-1012, August.
    3. Bornmann, Lutz & Tekles, Alexander & Zhang, Helena H. & Ye, Fred Y., 2019. "Do we measure novelty when we analyze unusual combinations of cited references? A validation study of bibliometric novelty indicators based on F1000Prime data," Journal of Informetrics, Elsevier, vol. 13(4).
    4. Bornmann, Lutz & Haunschild, Robin, 2015. "Which people use which scientific papers? An evaluation of data from F1000 and Mendeley," Journal of Informetrics, Elsevier, vol. 9(3), pages 477-487.
    5. Bornmann, Lutz & Haunschild, Robin, 2018. "Normalization of zero-inflated data: An empirical analysis of a new indicator family and its use with altmetrics data," Journal of Informetrics, Elsevier, vol. 12(3), pages 998-1011.
    6. Bornmann, Lutz & Marx, Werner, 2015. "Methods for the generation of normalized citation impact scores in bibliometrics: Which method best reflects the judgements of experts?," Journal of Informetrics, Elsevier, vol. 9(2), pages 408-418.
    7. Peiling Wang & Joshua Williams & Nan Zhang & Qiang Wu, 2020. "F1000Prime recommended articles and their citations: an exploratory study of four journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 933-955, February.
    8. Wang, Peiling & Su, Jing, 2021. "Post-publication expert recommendations in faculty opinions (F1000Prime): Recommended articles and citations," Journal of Informetrics, Elsevier, vol. 15(3).
    9. Mojisola Erdt & Aarthy Nagarajan & Sei-Ching Joanna Sin & Yin-Leng Theng, 2016. "Altmetrics: an analysis of the state-of-the-art in measuring research impact on social media," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1117-1166, November.
    10. Linhong Xu & Kun Ding & Yuan Lin & Chunbo Zhang, 2023. "Does citation polarity help evaluate the quality of academic papers?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 4065-4087, July.

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