Title: The Accuracy of Confidence Intervals for Field Normalised Indicators,
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.