Reformulating the meta-analytical random effects model of the standardized mean difference as a mixture model.

ABSTRACT: The classical meta-analytical random effects model (REM) has some weaknesses when applied to the standardized mean difference, g. Essentially, the variance of the studies involved is taken as the conditional variance, given a δ value, instead of the unconditional variance. As a consequence, the estimators of the variances involve a dependency between the g values and their variances that distorts the estimates. The classical REM is expressed as a linear model and the variance of g is obtained through a framework of components of variance. Although the weaknesses of the REM are negligible in practical terms in a wide range of realistic scenarios, all together, they make up an approximate, simplified version of the meta-analytical random effects model. We present an alternative formulation,

SUBMITTER: Suero M 

PROVIDER: S-EPMC11761815 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature