Threats to Internal Validity in Multiple-Baseline Design Variations
Nonconcurrent multiple-baseline designs can reach full internal validity if you stack enough within-tier replications.
01Research in Context
What this study did
Slocum et al. (2022) looked at nonconcurrent multiple-baseline designs. These are studies where each tier starts at a different time.
The authors asked: Do we have to run all tiers at the same time to be sure the treatment really works? They mapped out how within-tier replications can guard against history effects.
What they found
The paper argues that nonconcurrent designs can be just as strong as concurrent ones. The trick is to add enough within-tier replications.
When each tier shows the same jump after the intervention, the timing gaps matter less. History threats shrink because the pattern repeats.
How this fits with other research
Kratochwill et al. (2022) agree that nonconcurrent designs can be fixed, but they still prefer concurrent setups. They tell you to randomize start points and pile on tiers.
Petursdottir et al. (2018) gave the field a validity-threat checklist. Slocum uses that same list to show nonconcurrent MBD can check every box when replications are strong.
The two 2022 papers look like they clash: one says nonconcurrent is fine, the other says "use only if you must." The gap is policy, not science. Both accept the same replication fix.
Why it matters
If you run single-case studies, you can stop waiting for perfect calendar alignment. Add three or more within-tier replications and your nonconcurrent MBD still earns the blue ribbon for internal validity. That frees you to start tiers when clients are ready, not when the semester clock says so.
Want CEUs on This Topic?
The ABA Clubhouse has 60+ free CEUs — live every Wednesday. Ethics, supervision & clinical topics.
Join Free →Add one extra replication tier to your next multiple-baseline study before you start.
02At a glance
03Original abstract
Multiple baseline designs—both concurrent and nonconcurrent—are the predominant experimental design in modern applied behavior analytic research and are increasingly employed in other disciplines. In the past, there was significant controversy regarding the relative rigor of concurrent and nonconcurrent multiple baseline designs. The consensus in recent textbooks and methodological papers is that nonconcurrent designs are less rigorous than concurrent designs because of their presumed limited ability to address the threat of coincidental events (i.e., history). This skepticism of nonconcurrent designs stems from an emphasis on the importance of across-tier comparisons and relatively low importance placed on replicated within-tier comparisons for addressing threats to internal validity and establishing experimental control. In this article, we argue that the primary reliance on across-tier comparisons and the resulting deprecation of nonconcurrent designs are not well-justified. In this article, we first define multiple baseline designs, describe common threats to internal validity, and delineate the two bases for controlling these threats. Second, we briefly summarize historical methodological writing and current textbook treatment of these designs. Third, we explore how concurrent and nonconcurrent multiple baselines address each of the main threats to internal validity. Finally, we make recommendations for more rigorous use, reporting, and evaluation of multiple baseline designs.
Perspectives on Behavior Science, 2022 · doi:10.1007/s40614-022-00326-1