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Robust Rankings; Review of multivariate assessments illustrated by the Shanghai rankings

[journal article]

Freyer, Leo

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


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Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.
 

 

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