Letter to the editor: The unit-of-analysis error in meta-analysis: Why univariate tests cannot substitute for robust methodological synthesis

Meta-analytic modelling has long been a source of debate and continuous refinement, precisely because it must account for multiple interrelated factors: between-study heterogeneity, study weighting, confidence interval computation, and estimator choice, among others. Each of these components is designed to converge on a single goal—producing a robust, reproducible, and clinically meaningful inference from disparate studies. By contrast, univariate statistical tests are indispensable tools in clinical research, yet their scope is fundamentally different: they assess isolated comparisons, not aggregate effect estimates across heterogeneous datasets.