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Confidence Intervals for Relative Intensity of Collaboration (RIC) Indicators Cover

Confidence Intervals for Relative Intensity of Collaboration (RIC) Indicators

Open Access
|Oct 2022

Abstract

Purpose

We aim to extend our investigations related to the Relative Intensity of Collaboration (RIC) indicator, by constructing a confidence interval for the obtained values.

Design/methodology/approach

We use Mantel-Haenszel statistics as applied recently by Smolinsky, Klingenberg, and Marx.

Findings

We obtain confidence intervals for the RIC indicator

Research limitations

It is not obvious that data obtained from the Web of Science (or any other database) can be considered a random sample.

Practical implications

We explain how to calculate confidence intervals. Bibliometric indicators are more often than not presented as precise values instead of an approximation depending on the database and the time of measurement. Our approach presents a suggestion to solve this problem.

Originality/value

Our approach combines the statistics of binary categorical data and bibliometric studies of collaboration.

DOI: https://doi.org/10.2478/jdis-2022-0021 | Journal eISSN: 2543-683X | Journal ISSN: 2096-157X
Language: English
Page range: 5 - 15
Submitted on: Jul 30, 2022
Accepted on: Sep 27, 2022
Published on: Oct 19, 2022
Published by: Chinese Academy of Sciences, National Science Library
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2022 Joel Emanuel Fuchs, Lawrence Smolinsky, Ronald Rousseau, published by Chinese Academy of Sciences, National Science Library
This work is licensed under the Creative Commons Attribution 4.0 License.