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This paper introduces metapack, an R package simplifying complex meta-analysis and network meta-analysis. It offers flexible modeling and visualization tools for researchers, enhancing data synthesis and statistical inference.

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Area of Science:

  • Biostatistics
  • Statistical Modeling
  • Data Synthesis

Background:

  • Meta-analysis is a statistical method for combining research findings.
  • Aggregate data meta-analyses offer flexibility and are widely used.
  • Complex statistical models hinder the adoption of advanced meta-analysis techniques.

Purpose of the Study:

  • To introduce the R package metapack.
  • To provide a unified formula interface for meta-analysis and network meta-analysis.
  • To facilitate flexible variance-covariance modeling for multivariate and univariate network meta-analysis.

Main Methods:

  • Development of the R package metapack.
  • Implementation of a unified formula interface for meta-analysis and network meta-analysis.
  • Inclusion of functions for plotting and statistical inference, including model assessment.

Main Results:

  • The metapack package offers a user-friendly interface for complex meta-analysis models.
  • Flexible variance-covariance modeling is supported for multivariate meta-analysis and univariate network meta-analysis.
  • Demonstration of use cases with two real datasets included in the package.

Conclusions:

  • Metapack simplifies the application of advanced meta-analysis and network meta-analysis techniques.
  • The package enhances statistical inference and model assessment capabilities.
  • Metapack promotes wider adoption of sophisticated meta-analysis methods in research.