Masters candidate in Biostatistics, Ziren Jiang, will present:

“Estimating the Reference Interval from a Meta-analysis using Quantile Regression”

Plan B Adviser: Lianne Siegel

Abstract: Reference intervals, which define an interval in which a specific proportion of measurements from a healthy population are expected to fall, are commonly used in medical practice. Synthesizing information from multiple studies through meta-analysis can provide a more precise and representative reference interval than one derived from a single study. However, the current approaches for estimating the reference interval from a meta-analysis mainly rely on aggregate data and require parametric distributional assumptions that cannot always be checked. With the availability of individual participant data (IPD), non-parametric methods can be used to estimate reference intervals without any distributional assumptions. This paper introduces quantile regression as a method to estimate the reference interval from an IPD meta-analysis under the fixed effects model. A non-parametric bootstrap method is identified through a simulation study to account for within-study correlation when conducting inference. An example of liver stiffness measurements is provided to demonstrate the use of quantile regression in estimating reference intervals.