Abstract
<p>The multiple-baseline design (MBD) is the most commonly used type of single-case experimental design (SCED) in the behavioral sciences. In the context of recent discussions regarding the usefulness and internal validity of concurrent and nonconcurrent MBDs, we suggest a data analytical and graphical approach for concurrent MBDs using counterfactuals, allowing for within- and between-series comparisons. The data analytical approach is linked to principles from the existing SCED literature: selecting a quantification of effect that represents the researchers’ expectations about the data pattern, focusing on tentative causal inference, and summarizing the results without losing sight of the variability across series (i.e., tiers). The approach is formalized as a series of four steps, highlighting counterfactuals and a proposed graphical representation. The steps and the suggested plot are illustrated in the context of real-world data and can easily be implemented using the R code developed for providing both the numerical results and graphs.</p>