Academic Journal

Meta-analytic pooling of intraclass correlation coefficient estimates.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Meta-analytic pooling of intraclass correlation coefficient estimates.
Συγγραφείς: Bhat BH; Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, Netherlands.; Educational Psychology, The University of Texas at Austin, USA., Beretvas SN; Educational Psychology, The University of Texas at Austin, USA.
Πηγή: Research synthesis methods [Res Synth Methods] 2026 Sep; Vol. 17 (5), pp. 850-883. Date of Electronic Publication: 2026 Mar 30.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Wiley Blackwell Country of Publication: England NLM ID: 101543738 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1759-2887 (Electronic) Linking ISSN: 17592879 NLM ISO Abbreviation: Res Synth Methods Subsets: MEDLINE
Imprint Name(s): Publication: : Chichester : Wiley Blackwell
Original Publication: Malden, MA : John Wiley & Sons, 2010-
Ιατρικοί όροι (MeSH): Meta-Analysis as Topic*, Reproducibility of Results ; Data Interpretation, Statistical ; Humans ; Cluster Analysis ; Models, Statistical ; Algorithms ; Research Design ; Psychometrics ; Computer Simulation ; Sample Size
Περίληψη: Intraclass correlation coefficient (ICC) estimates are necessary for several statistical techniques. Researchers need accurate ICC estimates when conducting prospective power analyses for clustered data scenarios. In addition, meta-analysts require reasonable ICC values when adjusting effect size estimates to account for clustered primary study data or to correct for psychometric artifacts when using the ICC as a reliability measure. The validity of these analyses hinges on the accuracy of the ICC estimate. Beyond these secondary analyses, ICC estimates have been used as the focal outcome of meta-analysis itself to obtain a pooled measure of agreement, reliability, or the influence of a cluster's effect. This study evaluates how well meta-analytically pooled ICC estimates recover the population ICC parameter value when using different ICC variance formulas as the inverse variance weights used in the pooling. We found that the variance formula that uses a normalizing transformation performs best across most conditions.
Contributed Indexing: Keywords: cluster; intraclass correlation coefficient; meta-analysis; power analysis; reliability
Entry Date(s): Date Created: 20260330 Date Completed: 20260827 Latest Revision: 20260909
Update Code: 20260909
DOI: 10.1017/rsm.2026.10077
PMID: 41909970
Βάση Δεδομένων: MEDLINE