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Cross-hairs: a scatterplot for meta-analysis in R.

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Summary
This summary is machine-generated.

This study introduces a novel meta-analytic scatterplot, visualizing precision for paired variables, akin to diagnostic testing plots. The R program offers enhanced data visualization for meta-analysis, including effect sizes and shrunken estimates.

Keywords:
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Area of Science:

  • Biostatistics
  • Medical Informatics
  • Data Visualization

Background:

  • Meta-analysis requires robust visualization tools to assess the precision and relationships between variables across studies.
  • Existing methods may not adequately display the nuances of paired data or diagnostic testing metrics within a meta-analytic framework.

Purpose of the Study:

  • To introduce a novel meta-analytic scatterplot designed to display the precision of paired variables within studies.
  • To present an R-based program that enhances meta-analysis by offering advanced visualization options.

Main Methods:

  • Development of a meta-analytic scatterplot, functionally similar to a 'cross-hairs' plot used in diagnostic testing.
  • Inclusion of optional features such as boxplots for variable distributions, means, and correlation coefficients.
  • The program is implemented in R, allowing for user modification and integration with existing meta-analysis software.

Main Results:

  • The scatterplot effectively indicates the precision of paired variables, with an option to suppress 'cross-hairs' for dense data.
  • Demonstration of novel applications using independent and dependent effect sizes, as well as shrunken estimates.
  • The R program serves as a versatile companion tool for various meta-analysis approaches.

Conclusions:

  • The developed meta-analytic scatterplot provides a valuable tool for visualizing paired variable precision and relationships.
  • The R program offers flexibility and enhanced capabilities for researchers conducting meta-analyses, particularly with complex effect size data.