Liu, W;
Bretz, F;
Cortina-Borja, M;
(2020)
Reference range: Which statistical intervals to use?
Statistical Methods in Medical Research
10.1177/0962280220961793.
(In press).
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Abstract
Reference ranges, which are data-based intervals aiming to contain a pre-specified large proportion of the population values, are powerful tools to analyse observations in clinical laboratories. Their main point is to classify any future observations from the population which fall outside them as atypical and thus may warrant further investigation. As a reference range is constructed from a random sample from the population, the event ‘a reference range contains (100 P)% of the population’ is also random. Hence, all we can hope for is that such event has a large occurrence probability. In this paper we argue that some intervals, including the P prediction interval, are not suitable as reference ranges since there is a substantial probability that these intervals contain less than (100 P)% of the population, especially when the sample size is large. In contrast, a (P,γ) tolerance interval is designed to contain (100 P)% of the population with a pre-specified large confidence γ so it is eminently adequate as a reference range. An example based on real data illustrates the paper’s key points.
| Type: | Article |
|---|---|
| Title: | Reference range: Which statistical intervals to use? |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1177/0962280220961793 |
| Publisher version: | https://doi.org/10.1177/0962280220961793 |
| Language: | English |
| Additional information: | This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
| Keywords: | Nonparametric prediction interval, nonparametric tolerance interval, prediction interval, reference range, tolerance interval |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10112818 |
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