Zejnullahi R, Hedges LV. Robust variance estimation in
small meta-analysis with the standardized mean difference.
Res Synth Methods 2024;
15:44-60. [PMID:
37717978 DOI:
10.1002/jrsm.1668]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 08/15/2023] [Accepted: 08/15/2023] [Indexed: 09/19/2023]
Abstract
Conventional random-effects models in meta-analysis rely on large sample approximations instead of exact small sample results. While random-effects methods produce efficient estimates and confidence intervals for the summary effect have correct coverage when the number of studies is sufficiently large, we demonstrate that conventional methods result in confidence intervals that are not wide enough when the number of studies is small, depending on the configuration of sample sizes across studies, the degree of true heterogeneity and number of studies. We introduce two alternative variance estimators with better small sample properties, investigate degrees of freedom adjustments for computing confidence intervals, and study their effectiveness via simulation studies.
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