The Misspecification of the Covariance Structures in Multilevel Models for Single-Case Data: A Monte Carlo Simulation Study |
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| Authors: | Mariola Moeyaert Maaike Ugille John M Ferron S Natasha Beretvas Wim Van den Noortgate |
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| Institution: | 1. State University of New York at Albany;2. University of Leuven, Belgium;3. University of South Florida, Tampa;4. University of Texas, Austin;5. Katholieke Universiteit Leuven, Belgium |
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| Abstract: | The impact of misspecifying covariance matrices at the second and third levels of the three-level model is evaluated. Results indicate that ignoring existing covariance has no effect on the treatment effect estimate. In addition, the between-case variance estimates are unbiased when covariance is either modeled or ignored. If the research interest lies in the between-study variance estimate, including at least 30 studies is warranted. Modeling covariance does not result in less biased between-study variance estimates as the between-study covariance estimate is biased. When the research interest lies in the between-case covariance, the model including covariance results in unbiased between-case variance estimates. The three-level model appears to be less appropriate for estimating between-study variance if fewer than 30 studies are included. |
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| Keywords: | covariance misspecification Monte Carlo simulation study multilevel modeling multiple-baseline across cases designs |
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