Design Effect in Multilevel Settings

A Commentary on a Latent Variable Modeling Procedure for Its Evaluation

Bibliographic Data

ID20285973
AuthorsTenko Raykov (0000-0002-8911-5116, Michigan State University, East Lansing, MI, USA, corresponding author), Christine Distefano (0000-0001-7504-6554, University of South Carolina, Columbia, SC, USA)
Year2022
Volume82
Issue5
Pages1020-1030
Publication date2022-10-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEducational and Psychological Measurement (JOURNAL)
Journal identifiersISSN: 0013-1644 • E-ISSN: 1552-3888
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/00131644211019447
PMID35989726
OpenAlexW3170017143
LanguageEN
Citations received1
References cited14

A latent variable modeling-based procedure is discussed that permits to readily point and interval estimate the design effect index in multilevel settings using widely circulated software. The method provides useful information about the relationship of important parameter standard errors when accounting for clustering effects relative to conducting single-level analyses. The approach can also be employed as an addendum to point and interval estimation of the intraclass correlation coefficient in empirical research. The discussed procedure makes it easily possible to evaluate the design effect in two-level studies by utilizing the popular latent variable modeling methodology and is illustrated with an example

Cluster analysis · Confidence interval · Data mining · Econometrics · Interval (graph theory) · Interval estimation · Intraclass correlation · Latent variable · Latent variable model · Multilevel model · Point (geometry) · Point estimation · Psychometrics · Statistics · Structural equation modeling · Variable (mathematics) · Advanced Statistical Modeling Techniques · Computer Science · Mathematics · Psychometric Methodologies and Testing · Statistical Methods and Bayesian Inference

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