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Bridging Guidelines and Practice: An Implementation Science Perspective on Statistical Rigor in Meta-Analysis

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Abstract

Meta-analysis has advanced rapidly over the past couple of decades, alongside significant improvements in its statistical approaches. However, despite expert recommendations, meta-reviews reveal a slow uptake of best practices among researchers. Building on a previous meta-review in K-12 education, this paper examined how published meta-analyses follow advanced statistical best practices such as dependent effect size models and the exploration of heterogeneity. Using frameworks from Implementation Science (IS) and the Diffusion of Innovation (DOI), this study investigated the adoption of these advanced methods and identified potential barriers to their broader implementation. Based on trends in published meta-analyses in this sample, this study proposes a DOI-informed framework for the research community on disseminating meta-analytic research methods more effectively.

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Date
2026-05
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Publisher
Research Projects
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Keywords
meta-analysis, dependent effect sizes, meta-regression, implementation science
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2027-05
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