Title: Estimating causal effects from multiple-baseline studies: Implications for design and analysis
Authors: Ferron, John ×
Moeyaert, Mariola
Van Den Noortgate, Wim
Beretvas, S. Natasha #
Issue Date: Dec-2014
Publisher: American Psychological Association
Series Title: Psychological Methods vol:19 issue:4 pages:493-510
Abstract: Traditionally, average causal effects from multiple-baseline data are estimated by aggregating individual causal effect estimates obtained through within-series comparisons of treatment-phase trajectories to baseline extrapolations. Concern that these estimates may be biased due to event effects, such as history and maturation, motivates our proposal of a between-series estimator that contrasts participants in the treatment to those in the baseline phase. Accuracy of the new method was assessed and compared in a series of simulation studies where participants were randomly assigned to intervention start points. The within-series estimator was found to have greater power to detect treatment effects but also to be biased due to event effects, leading to faulty causal inferences. The between-series estimator remained unbiased and controlled the Type I error rate independent of event effects. Because the between-series estimator is unbiased under different assumptions, the two estimates complement each other, and the difference between them can be used to detect inaccuracies in the modeling assumptions. The power to detect inaccuracies associated with event effects was found to depend on the size and type of event effect. We empirically illustrate the methods using a real dataset and then discuss implications for researchers planning multiple-baseline studies.
ISSN: 1082-989X
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Methodology of Educational Sciences
Faculty of Psychology and Educational Sciences, Campus Kulak Kortrijk – miscellaneous
Faculty of Psychology and Educational Sciences - miscellaneous
× corresponding author
# (joint) last author

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