title: The use of multilevel analysis for integrating single-case experimental design results within a study and across studies.
abstract: The use of multilevel models as a method for synthesising single-case experimental design results is receiving increased consideration. In this article we discuss the potential advantages and limitations of the multilevel modelling approach. We present a basic two-level model where observations are nested within cases, and then discuss extensions of the basic model to accommodate trends, moderators of the intervention effect, non-continuous outcomes, heterogeneity, autocorrelation, the nesting of cases within studies, and more complex single-case design types. We then consider methods for standardising the effect estimates and alternative approaches to estimating the models. These modelling and analysis options are followed by an illustrative example.
authors.affiliation: a University of South Florida , Tampa , FL , USA.
authors.forename: Eun Kyeng
authors.initials: EK
authors.lastname: Baek
authors.forename: Mariola
authors.initials: M
authors.lastname: Moeyaert
authors.forename: Merlande
authors.initials: M
authors.lastname: Petit-Bois
authors.forename: S Natasha
authors.initials: SN
authors.lastname: Beretvas
authors.forename: Wim
authors.initials: W
authors.lastname: Van den Noortgate
authors.forename: John M
authors.initials: JM
authors.lastname: Ferron
mesh_terms: D006801:Humans; D015233:Models, Statistical; D055361:Multilevel Analysis / Q000379:methods*; D012107:Research Design / Q000706:statistics & numerical data*; D013223:Statistics as Topic / Q000379:methods*
keywords: Effect size; Intervention effect; Multilevel modelling; Single-case experimental design; Standardisation