Researcher capacity estimation based on the Q model: a generalized linear mixed model perspective
Author
Abstract
Suggested Citation
DOI: 10.1007/s11192-023-04756-9
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- James Hartley, 2017. "Authors and their citations: a point of view," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 1081-1084, February.
- Mutz, Rüdiger & Daniel, Hans-Dieter, 2019. "How to consider fractional counting and field normalization in the statistical modeling of bibliometric data: A multilevel Poisson regression approach," Journal of Informetrics, Elsevier, vol. 13(2), pages 643-657.
- Lu Liu & Yang Wang & Roberta Sinatra & C. Lee Giles & Chaoming Song & Dashun Wang, 2018. "Hot streaks in artistic, cultural, and scientific careers," Nature, Nature, vol. 559(7714), pages 396-399, July.
- Pedro Alvarez & Antonio Pulgarín, 1996. "The Rasch model. Measuring the impact of scientific journals: Analytical chemistry," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 47(6), pages 458-467, June.
- Mutz, Rüdiger & Daniel, Hans-Dieter, 2018. "The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model," Journal of Informetrics, Elsevier, vol. 12(4), pages 1282-1295.
- Boris Forthmann & Philipp Doebler, 2021. "Reliability of researcher capacity estimates and count data dispersion: a comparison of Poisson, negative binomial, and Conway-Maxwell-Poisson models," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3337-3354, April.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Lin Zhang & Yuanyuan Shang & Ying Huang & Gunnar Sivertsen, 2022. "Gender differences among active reviewers: an investigation based on publons," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 145-179, January.
- Yu, Shuo & Alqahtani, Fayez & Tolba, Amr & Lee, Ivan & Jia, Tao & Xia, Feng, 2022. "Collaborative Team Recognition: A Core Plus Extension Structure," Journal of Informetrics, Elsevier, vol. 16(4).
- Mutz, Rüdiger & Daniel, Hans-Dieter, 2018. "The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model," Journal of Informetrics, Elsevier, vol. 12(4), pages 1282-1295.
- Wu, Lingfei & Kittur, Aniket & Youn, Hyejin & Milojević, Staša & Leahey, Erin & Fiore, Stephen M. & Ahn, Yong-Yeol, 2022. "Metrics and mechanisms: Measuring the unmeasurable in the science of science," Journal of Informetrics, Elsevier, vol. 16(2).
- Wen Lou & Jiangen He & Lingxin Zhang & Zhijie Zhu & Yongjun Zhu, 2023. "Support behind the scenes: the relationship between acknowledgement, coauthor, and citation in Nobel articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5767-5790, October.
- Yue Wang & Ning Li & Bin Zhang & Qian Huang & Jian Wu & Yang Wang, 2023. "The effect of structural holes on producing novel and disruptive research in physics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1801-1823, March.
- Wolfgang Glänzel & Henk F. Moed, 2013. "Opinion paper: thoughts and facts on bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 381-394, July.
- Yu, Xiaoyao & Szymanski, Boleslaw K. & Jia, Tao, 2021. "Become a better you: Correlation between the change of research direction and the change of scientific performance," Journal of Informetrics, Elsevier, vol. 15(3).
- Krzysztof Rusek & Agnieszka Kleszcz & Albert Cabellos-Aparicio, 2023. "Bayesian inference of spatial and temporal relations in AI patents for EU countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3313-3335, June.
- Zhang, Lin & Shang, Yuanyuan & HUANG, Ying & Sivertsen, Gunnar, 2021. "Gender differences among active reviewers: an investigation based on Publons," SocArXiv 4z6w8, Center for Open Science.
- Vitalis, Kyriacos & Stefanidis, Dimosthenis & Pallis, George & Dikaiakos, Marios & Nicolaou, Nicos & Nicolaides, Christos, 2024. "Quantifying the impact of online social networks on the success of entrepreneurs," OSF Preprints x6vda, Center for Open Science.
- Boris Forthmann & Mark A. Runco, 2020. "An Empirical Test of the Inter-Relationships between Various Bibliometric Creative Scholarship Indicators," Publications, MDPI, vol. 8(2), pages 1-16, June.
- Zhu, Wanying & Jin, Ching & Ma, Yifang & Xu, Cong, 2023. "Earlier recognition of scientific excellence enhances future achievements and promotes persistence," Journal of Informetrics, Elsevier, vol. 17(2).
- Petersen, Alexander M. & Penner, Orion, 2020. "Renormalizing individual performance metrics for cultural heritage management of sports records," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
- Aliakbar Akbaritabar & Andrés F. Castro Torres & Vincent Larivière, 2023. "A global perspective on the social structure of science," MPIDR Working Papers WP-2023-029, Max Planck Institute for Demographic Research, Rostock, Germany.
- Liu, Meijun & Jaiswal, Ajay & Bu, Yi & Min, Chao & Yang, Sijie & Liu, Zhibo & Acuña, Daniel & Ding, Ying, 2022. "Team formation and team impact: The balance between team freshness and repeat collaboration," Journal of Informetrics, Elsevier, vol. 16(4).
- Zhang, Yang & Wang, Yang & Du, Haifeng & Havlin, Shlomo, 2024. "Delayed citation impact of interdisciplinary research," Journal of Informetrics, Elsevier, vol. 18(1).
- Bornmann, Lutz & Haunschild, Robin & Mutz, Rüdiger, 2020. "Should citations be field-normalized in evaluative bibliometrics? An empirical analysis based on propensity score matching," Journal of Informetrics, Elsevier, vol. 14(4).
- Dosso, Dennis & Silvello, Gianmaria, 2020. "Data credit distribution: A new method to estimate databases impact," Journal of Informetrics, Elsevier, vol. 14(4).
- Yu, Dejian & Pan, Tianxing, 2021. "Tracing the main path of interdisciplinary research considering citation preference: A case from blockchain domain," Journal of Informetrics, Elsevier, vol. 15(2).
More about this item
Keywords
Q model; Researcher capacity; Generalized linear mixed model;All these keywords.
JEL classification:
- C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:128:y:2023:i:8:d:10.1007_s11192-023-04756-9. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.