Estimating the reference interval from a fixed effects meta-analysis

Wenhao Cao, Lianne Siegel, Jincheng Zhou, Motao Zhu, Tiejun Tong, Yong Chen, Haitao Chu

Research output: Contribution to journalArticlepeer-review


A reference interval provides a basis for physicians to determine whether a measurement is typical of a healthy individual. It can be interpreted as a prediction interval for a new individual from the overall population. However, a reference interval based on a single study may not be representative of the broader population. Meta-analysis can provide a general reference interval based on the overall population by combining results from multiple studies. Methods for estimating the reference interval from a random effects meta-analysis have been recently proposed to incorporate the within and between-study variation, but a random effects model may give imprecise estimates of the between-study variation with only few studies. In addition, the normal distribution of underlying study-specific means, and equal within-study variance assumption in these methods may be inappropriate in some settings. In this article, we aim to estimate the reference interval based on the fixed effects model assuming study effects are unrelated, which is useful for a meta-analysis with only a few studies (e.g., ≤5). We propose a mixture distribution method only assuming parametric distributions (e.g., normal) for individuals within each study and integrating them to form the overall population distribution. This method is compared to an empirical method only assuming a parametric overall population distribution. Simulation studies have shown that both methods can estimate a reference interval with coverage close to the targeted value (i.e., 95%). Meta-analyses of women daytime urination frequency and frontal subjective postural vertical measurements are reanalyzed to demonstrate the application of our methods.

Original languageEnglish (US)
Pages (from-to)630-640
Number of pages11
JournalResearch Synthesis Methods
Issue number5
Early online dateApr 17 2021
StatePublished - Sep 2021

Bibliographical note

Funding Information:
This research was funded in part by the U.S. National Institutes of Health's National Center for Advancing Translational Sciences grant UL1TR002494, National Library of Medicine grant R01LM012982, and NIH National Heart, Lung, and Blood Institute grant T32HL129956.

Publisher Copyright:
© 2021 John Wiley & Sons Ltd.


  • fixed effects model
  • meta-analysis
  • reference interval
  • very few studies

PubMed: MeSH publication types

  • Journal Article
  • Meta-Analysis


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