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MA-cont:pre/post effect size: An interactive tool for the meta-analysis of continuous outcomes using R Shiny.

Katerina Papadimitropoulou1, Richard D Riley2, Olaf M Dekkers1

  • 1Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.

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Summary
This summary is machine-generated.

This study introduces MA-cont:pre/post effect size, a free web tool for meta-analysis of continuous data. It simplifies combining evidence from pretest-posttest studies using various statistical methods.

Keywords:
ANCOVAbaseline imbalancepseudo individual participant datashiny

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Area of Science:

  • Biostatistics
  • Medical Research Methodology

Background:

  • Meta-analysis is crucial for synthesizing evidence from multiple studies, particularly in medicine to determine treatment effectiveness.
  • Analyzing continuous outcomes in pretest-posttest designs involves various methods like analyzing final scores, change scores, or analysis of covariance.
  • Existing statistical software often dictates method choice based on data availability and user preference.

Purpose of the Study:

  • To present MA-cont:pre/post effect size, a novel web-based tool for conducting meta-analyses of continuous data from pretest-posttest studies.
  • To offer a user-friendly platform that accommodates multiple analytical approaches for aggregate data and pseudo individual participant data.
  • To provide a free, no-coding-required solution for researchers, enhancing accessibility to advanced meta-analysis techniques.

Main Methods:

  • Development of an interactive web tool using R Shiny for meta-analysis of continuous outcomes.
  • Implementation of established methods: analysis of final scores, change scores, and analysis of covariance.
  • Inclusion of a flexible approach for generating and analyzing pseudo individual participant data.

Main Results:

  • The MA-cont:pre/post effect size tool offers a unified environment for diverse meta-analysis methods.
  • The tool is accessible via a web interface, requiring no programming expertise.
  • It supports both aggregate data analysis and pseudo individual participant data analysis.

Conclusions:

  • MA-cont:pre/post effect size democratizes meta-analysis of continuous pretest-posttest data.
  • The tool facilitates robust evidence synthesis by integrating multiple analytical strategies.
  • Researchers are encouraged to utilize this free resource, with a recommendation to consult experts for complex statistical understanding.