The Metric Comparability of Meta-Analytic Effect-Size Estimators From Factorial Designs.

Abstract

The primary studies in a meta-analysis of standardized mean differences generally include a mixture of single-factor t tests and multifactor analysis of variance designs. Accordingly, there is a need for effect-size measures in multifactor designs that are metrically comparable with measures in single-factor t tests. Two models, the variance-preservation model and the variance-reduction model, provide a formal description of the 2 principal routes by which a single-factor design may evolve into a higher order factorial design. New metrically comparable effect-size measures and estimators are developed for designs that contain variance-preservation factors, variance-reduction factors, or a mixture of both types of factors. A statistical test for checking the validity of model assumptions is presented.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 27 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.