Loading...
The Accuracy of Confidence Intervals for Field Normalised Indicators
Fairclough, Ruth
Fairclough, Ruth
Authors
Editors
Other contributors
Affiliation
Epub Date
Issue Date
2017-04-07
Submitted date
Alternative
Abstract
When comparing the average citation impact of research groups, universities and countries, field normalisation reduces the influence of discipline and time. Confidence intervals for these indicators can help with attempts to infer whether differences between sets of publications are due to chance factors. Although both bootstrapping and formulae have been proposed for these, their accuracy is unknown. In response, this article uses simulated data to systematically compare the accuracy of confidence limits in the simplest possible case, a single field and year. The results suggest that the MNLCS (Mean Normalised Log-transformed Citation Score) confidence interval formula is conservative for large groups but almost always safe, whereas bootstrap MNLCS confidence intervals tend to be accurate but can be unsafe for smaller world or group sample sizes. In contrast, bootstrap MNCS (Mean Normalised Citation Score) confidence intervals can be very unsafe, although their accuracy increases with sample sizes.
Citation
Thelwall, M. & Fairclough, R. (2017) The accuracy of confidence intervals for field normalised indicators, Journal of Informetrics, 11 (2) 530-540.
Publisher
Journal
Research Unit
PubMed ID
PubMed Central ID
Embedded videos
Additional Links
Type
Journal article
Language
en
Description
This is an accepted manuscript of an article published by Elsevier in Journal of Informetrics on 07/04/2017, available online: https://doi.org/10.1016/j.joi.2017.03.004
The accepted version of the publication may differ from the final published version.
Series/Report no.
ISSN
1875-5879