title: The influence of the design matrix on treatment effect estimates in the quantitative analyses of single-subject experimental design research.
abstract: The quantitative methods for analyzing single-subject experimental data have expanded during the last decade, including the use of regression models to statistically analyze the data, but still a lot of questions remain. One question is how to specify predictors in a regression model to account for the specifics of the design and estimate the effect size of interest. These quantitative effect sizes are used in retrospective analyses and allow synthesis of single-subject experimental study results which is informative for evidence-based decision making, research and theory building, and policy discussions. We discuss different design matrices that can be used for the most common single-subject experimental designs (SSEDs), namely, the multiple-baseline designs, reversal designs, and alternating treatment designs, and provide empirical illustrations. The purpose of this article is to guide single-subject experimental data analysts interested in analyzing and meta-analyzing SSED data.
authors.affiliation: Katholieke Universiteit Leuven, Belgium mariola.moeyaert@ppw.kuleuven.be.
authors.forename: Mariola
authors.initials: M
authors.lastname: Moeyaert
authors.affiliation: Katholieke Universiteit Leuven, Belgium.
authors.forename: Maaike
authors.initials: M
authors.lastname: Ugille
authors.affiliation: University of South Florida, Tampa, USA.
authors.forename: John M
authors.initials: JM
authors.lastname: Ferron
authors.affiliation: University of Texas, Austin, USA.
authors.forename: S Natasha
authors.initials: SN
authors.lastname: Beretvas
authors.affiliation: Katholieke Universiteit Leuven, Belgium.
authors.forename: Wim
authors.initials: W
authors.lastname: Van den Noortgate
mesh_terms: D006801:Humans; D012107:Research Design; D013223:Statistics as Topic
keywords: alternating treatment design; design matrix; multiple-baseline design; piecewise regression equation; reversal design; single-subject experimental design