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The standardized mean difference has been widely used as the most common index of effect magnitude in many applied fields. In this paper, we propose a novel approach using the concept of generalized variable for the confidence interval estimation and hypothesis testing of standardized mean difference. Furthermore, we extend this approach to compare standardized mean differences between two studies or between two strata. Simulation results demonstrate that the proposed approach can provide confidence intervals with excellent coverage properties and can perform hypothesis testing with satisfactory type-I error control.
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Stored only when both papers are in the corpus — 16 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.