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Diagnostic test accuracy: application and practice using R software.

Sung Ryul Shim1,2, Seong-Jang Kim3,4, Jonghoo Lee5

  • 1Department of Preventive Medicine, Korea University College of Medicine, Seoul, Korea.

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|April 20, 2019
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Summary
This summary is machine-generated.

This guide explains how to use R software for diagnostic test accuracy (DTA) meta-analysis. It details practical methods for synthesizing DTA data, making it accessible for non-statisticians.

Keywords:
Diagnostic test accuracyLikelihood ratiosMadaMeta-analysisReceiver-operating characteristic curveReitsma

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Area of Science:

  • Medical Statistics
  • Health Research Methodology

Background:

  • Diagnostic test accuracy (DTA) synthesis is crucial for evidence-based medicine.
  • Quantitative synthesis of DTA data often requires specialized statistical software.
  • Researchers, particularly those outside statistics, may find DTA meta-analysis complex.

Purpose of the Study:

  • To describe practical approaches for quantitative synthesis of diagnostic test accuracy data using R software.
  • To provide guidance on utilizing specific R packages for DTA meta-analysis.
  • To simplify DTA calculations for researchers in non-statistical fields.

Main Methods:

  • Utilized R software for univariate and bivariate analysis of DTA.
  • Employed R packages including "metaprop", "metabin", "mada", and "metareg".
  • Focused on calculating effect sizes, assessing heterogeneity, and generating summarized ROC curves.

Main Results:

  • Demonstrated R commands for calculating sensitivity, specificity, and diagnostic odds ratio.
  • Illustrated the creation of forest plots and summarized ROC curves.
  • Provided practical steps for meta-regression analysis in DTA.

Conclusions:

  • R software offers accessible tools for conducting DTA meta-analysis.
  • This approach empowers non-statisticians to perform quantitative DTA synthesis.
  • Encourages wider adoption of R for DTA research, fostering increased interest.