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Activity Number:
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423
- Topics in Health Services Research: Meta-Analysis, Health Care Disparities, and Observational Data
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Type:
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Contributed
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Date/Time:
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Wednesday, August 10, 2022 : 10:30 AM to 12:20 PM
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Sponsor:
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Health Policy Statistics Section
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Abstract #322594
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Title:
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RIMeta: A Shiny App for Estimating Reference Interval from Meta-Analysis
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Author(s):
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Ziren Jiang* and Wenhao Cao and Haitao Chu and Lianne Siegel
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Companies:
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University of Minnesota and Division of Biostatistics, University of Minnesota and Pfizer Inc. and University of Minnesota
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Keywords:
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meta-analysis;
reference interval;
aggregate data;
R Shiny
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Abstract:
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A reference interval, or an interval in which a pre-specified proportion of measurements from a healthy population are expected to fall, can be used to determine whether a person’s measurement is typical of a healthy individual. For a specific biomarker, multiple studies may provide data collected from healthy participants. A reference interval estimated by combining the data across these studies typically is more generalizable than a reference interval based on a single study. Methods for estimating reference intervals from random effects and fixed effects meta-analysis have been recently proposed and implemented using R software. We present an R-Shiny tool RIMeta implementing these methods, which allows users not proficient in R to estimate a reference interval from a meta-analysis using aggregated data from each study. RIMeta provides users a convenient way to estimate a reference interval from a meta-analysis and to generate a forest plot illustrating the results. The use of this web-based R Shiny tool does not require the installation of R or any background knowledge of programming. We explain all functions of the RIMeta and illustrate how to use it with a real data example.
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Authors who are presenting talks have a * after their name.
