Alternative tests and measures for between-study inconsistency in meta-analysis.

ABSTRACT: Meta-analysis is a widely used method for synthesizing results from multiple studies across diverse fields. A central challenge in meta-analysis is assessing between-study inconsistency, which can arise from differences in study populations, methodological heterogeneity, or the presence of outliers. Conventional tools such as the [Formula: see text] and [Formula: see text] statistics could be limited in power, especially when the number of studies is small or when the between-study distribution deviates from normality. To address these limitations, we propose a family of alternative [Formula: see text]-like statistics and a hybrid test that adaptively combines their strengths. We also introduce new measures to quantify inconsistency based on these statistics. Simulation studies demonstrate

SUBMITTER: Yu Z 

PROVIDER: S-EPMC12632047 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature