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MSE FINDR: A Shiny R Application to Estimate Mean Square Error Using Treatment Means and Post Hoc Test Results.

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Summary

Researchers can now estimate missing within-study variance using the MSE FINDR application. This tool enhances meta-analysis by including studies previously excluded due to incomplete variance data, improving statistical power and reducing bias.

Keywords:
R Shinymeta-analysismissing summary statisticsresidual variance recoveryunreported variability

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Area of Science:

  • Biostatistics and Research Synthesis
  • Statistical Software Development

Background:

  • Meta-analysis and research synthesis require summary statistics, primarily means and variance, for accurate conclusions.
  • A common challenge is the absence of explicit within-study variance in published studies, leading to their exclusion and potential biases like small-study effects.

Purpose of the Study:

  • To introduce MSE FINDR, a user-friendly Shiny R application designed to estimate mean square error (within-study residual variance) for continuous outcomes.
  • To enable the inclusion of studies with missing variance data in meta-analyses, thereby increasing statistical power and reducing bias.

Main Methods:

  • MSE FINDR estimates within-study variance ([Formula: see text]) for various analysis of variance (ANOVA)-type experimental designs (e.g., Latin square, factorial, split-plot).
  • The application utilizes commonly reported data: treatment means, significance level (α), number of replicates, and post hoc mean separation tests (LSD, Tukey's HSD, Bonferroni, Šidák, Scheffé).
  • Users upload study data as a CSV file, specify the experimental design and post hoc test, and MSE FINDR recovers the missing variance.

Main Results:

  • Simulations demonstrated that MSE FINDR accurately predicts the actual ANOVA within-study variance for one-way and two-way experimental designs.
  • The accuracy of recovered variance was consistent across different post hoc tests and experimental designs, including split-plot designs.
  • The recovered within-study variance can be downloaded as a CSV file for subsequent meta-analysis.

Conclusions:

  • MSE FINDR effectively estimates missing within-study variance from readily available summary statistics in published research.
  • This tool facilitates the inclusion of valuable studies previously excluded from meta-analyses, enhancing the robustness of synthesized findings.
  • The application is accessible online with comprehensive documentation and tutorials to support its widespread adoption by researchers.