Obtaining Sound Intraclass Correlation and Variance Estimates in Three-Level Models: The Role of Sampling-Strategies

Abstract: Three-level clustered data commonly occur in social and behavioral research and are prominently analyzed using multilevel modeling. The influence of the clustering on estimation results is assessed with the intraclass correlation coefficients (ICCs), which indicate the fraction of variance in the outcome located at each higher level. However, ICCs are prone to bias due to high requirements regarding the overall sample size and the sample size at each data level. In Monte Carlo simulations, we investigate how these sample characteristics influence the bias of the ICCs and statistical power of the variance components using robust ML-estimation. Results reveal considerable underestimation on Level-3 and the importance of the Level-3 sample size in combination with the ICC sizes. Based on our results, we derive concise sampling recommendations and discuss limits to our inferences. https://meth.psychopen.eu/index.php/meth/article/view/7265

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
Obtaining Sound Intraclass Correlation and Variance Estimates in Three-Level Models: The Role of Sampling-Strategies ; volume:18 ; number:1 ; day:31 ; month:03 ; year:2022
Methodology ; 18, Heft 1 (31.03.2022)

Urheber
Kerkhoff, Denise
Nussbeck, Fridtjof W.

DOI
10.5964/meth.7265
URN
urn:nbn:de:101:1-2022051405120884132777
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
15.08.2025, 07:33 MESZ

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