Heterogeneity estimation in meta-analysis of standardized mean differences when the distribution of random effects departs from normal: A Monte Carlo simulation study.

ABSTRACT:

Background

Advantages of meta-analysis depend on the assumptions underlying the statistical procedures used being met. One of the main assumptions that is usually taken for granted is the normality underlying the population of true effects in a random-effects model, even though the available evidence suggests that this assumption is often not met. This paper examines how 21 frequentist and 24 Bayesian methods, including several novel procedures, for computing a point estimate of the heterogeneity parameter ([Formula: see text]) perform when the distribution of random effects departs from normality compared to normal scenarios in meta-analysis of standardized mean differences.

Methods

A Monte Carlo simulation was carried out using the R software, generating data for meta-anal

SUBMITTER: Blazquez-Rincon D 

PROVIDER: S-EPMC9843903 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature