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Bornmann, L.; Mutz, R.; Daniel, H.D.: Do we need the h index and its variants in addition to standard bibliometric measures? (2009)
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- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.6, S.1286-1289
- Year
- 2009
-
Bornmann, L.; Daniel, H.-D.: Universality of citation distributions : a validation of Radicchi et al.'s relative indicator cf = c/c0 at the micro level using data from chemistry (2009)
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- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.8, S.1664-1670
- Year
- 2009
-
Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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- Date
- 18. 3.2014 19:13:22
-
Bornmann, L.: Lässt sich die Qualität von Forschung messen? (2013)
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- Source
- Wissen - Wissenschaft - Organisation: Proceedings der 12. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation Bonn, 19. bis 21. Oktober 2009. Hrsg.: H.P. Ohly
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Mutz, R.; Bornmann, L.; Daniel, H.-D.: Testing for the fairness and predictive validity of research funding decisions : a multilevel multiple imputation for missing data approach using ex-ante and ex-post peer evaluation data from the Austrian science fund (2015)
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- Abstract
- It is essential for research funding organizations to ensure both the validity and fairness of the grant approval procedure. The ex-ante peer evaluation (EXANTE) of N?=?8,496 grant applications submitted to the Austrian Science Fund from 1999 to 2009 was statistically analyzed. For 1,689 funded research projects an ex-post peer evaluation (EXPOST) was also available; for the rest of the grant applications a multilevel missing data imputation approach was used to consider verification bias for the first time in peer-review research. Without imputation, the predictive validity of EXANTE was low (r?=?.26) but underestimated due to verification bias, and with imputation it was r?=?.49. That is, the decision-making procedure is capable of selecting the best research proposals for funding. In the EXANTE there were several potential biases (e.g., gender). With respect to the EXPOST there was only one real bias (discipline-specific and year-specific differential prediction). The novelty of this contribution is, first, the combining of theoretical concepts of validity and fairness with a missing data imputation approach to correct for verification bias and, second, multilevel modeling to test peer review-based funding decisions for both validity and fairness in terms of potential and real biases.
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Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014)
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- Date
- 22. 8.2014 17:05:18
-
Bornmann, L.: How to analyze percentile citation impact data meaningfully in bibliometrics : the statistical analysis of distributions, percentile rank classes, and top-cited papers (2013)
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- Date
- 22. 3.2013 19:44:17
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Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019)
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- Date
- 8. 1.2019 18:22:45
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Leydesdorff, L.; Bornmann, L.: How fractional counting of citations affects the impact factor : normalization in terms of differences in citation potentials among fields of science (2011)
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- Date
- 22. 1.2011 12:51:07
