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Robust Rankings; Review of multivariate assessments illustrated by the Shanghai rankings
[journal article]
Abstract
Defined errors are entered into data collections in order to test their influence on the reliability of multivariate rankings. Random numbers and real ranking data serve as data origins. In the course of data collection small random errors often lead to a switch in ranking, which can influence the ... view more
Defined errors are entered into data collections in order to test their influence on the reliability of multivariate rankings. Random numbers and real ranking data serve as data origins. In the course of data collection small random errors often lead to a switch in ranking, which can influence the general ranking picture considerably. For stabilisation an objective weighting method is evaluated. The robustness of these rankings is then compared to the original forms. Robust forms of the published Shanghai top 100 rankings are calculated and compared to each other. As a result, the possibilities and restrictions of this type of weighting become recognisable.... view less
Keywords
ranking; data capture; weighting; error; scientometry
Classification
Scientometrics, Bibliometrics, Informetrics
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
objective weighting; fault tolerance; Shanghai ranking
Document language
English
Publication Year
2014
Page/Pages
p. 391-406
Journal
Scientometrics, 100 (2014) 2
DOI
https://doi.org/10.1007/s11192-014-1313-8
ISSN
1588-2861
Status
Published Version; peer reviewed
Licence
Creative Commons - Attribution