<abstract xmlns="http://www.w3.org/1999/xhtml">

<sec><h3>Purpose</h3>
<p>We aim to extend our investigations related to the Relative Intensity of Collaboration (RIC) indicator, by constructing a confidence interval for the obtained values.</p>
</sec>
<sec><h3>Design/methodology/approach</h3>
<p>We use Mantel-Haenszel statistics as applied recently by Smolinsky, Klingenberg, and Marx.</p>
</sec>
<sec><h3>Findings</h3>
<p>We obtain confidence intervals for the RIC indicator</p>
</sec>
<sec><h3>Research limitations</h3>
<p>It is not obvious that data obtained from the Web of Science (or any other database) can be considered a random sample.</p>
</sec>
<sec><h3>Practical implications</h3>
<p>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.</p>
</sec>
<sec><h3>Originality/value</h3>
<p>Our approach combines the statistics of binary categorical data and bibliometric studies of collaboration.</p>
</sec>
</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.

Confidence Intervals for Relative Intensity of Collaboration (RIC) Indicators

Journal of Data and Information Science

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Confidence Intervals for Relative Intensity of Collaboration (RIC) Indicators"}

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

Confidence Intervals for Relative Intensity of Collaboration (RIC) Indicators

Article Category: Letter

Online veröffentlicht: 19. Okt. 2022

Seitenbereich: 5 - 15

Eingereicht: 30. Juli 2022

Akzeptiert: 27. Sept. 2022

DOI: https://doi.org/10.2478/jdis-2022-0021

Schlüsselwörter
Contingency tables, Confidence intervals, Relative intensity of collaboration (RIC), Mantel-Haenszel statistics, Science of science

© 2022 Joel Emanuel Fuchs et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Confidence Intervals for Relative Intensity of Collaboration (RIC) Indicators

Article Category: Letter

Online veröffentlicht: 19. Okt. 2022

Seitenbereich: 5 - 15

Eingereicht: 30. Juli 2022

Akzeptiert: 27. Sept. 2022

DOI: https://doi.org/10.2478/jdis-2022-0021

SchlüsselwörterContingency tables, Confidence intervals, Relative intensity of collaboration (RIC), Mantel-Haenszel statistics, Science of science

© 2022 Joel Emanuel Fuchs et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Contingency tables, Confidence intervals, Relative intensity of collaboration (RIC), Mantel-Haenszel statistics, Science of science