Multiple Baseline Design — Single-Subject Experimental Design
Multiple Baseline Single-Subject Experimental Design · Also known as: MBD, multiple-baseline single-case design, staggered baseline design, multiple-probe design
The multiple baseline design is a single-subject experimental design that demonstrates functional control by introducing an intervention at staggered time points across two or more baselines — typically across different behaviors, individuals, or settings. Because no withdrawal of treatment is required, it is especially suitable when the target behavior is irreversible or when removing an effective intervention would be unethical.
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When to use it
Use a multiple baseline design when the target behavior is expected to be irreversible once learned (e.g., reading skills, social skills acquisition), making a withdrawal design unethical or impractical. It is well suited when you can identify at least two or three conceptually similar, functionally independent tiers (behaviors, participants, or settings) that share the same intervention logic. Minimum requirement: at least two tiers with stable baselines of at least three to five data points each. Do not use this design if the tiers are not independent — concurrent improvement across all tiers during any single baseline phase undermines the logic of the staggered demonstration. Also avoid it when the intervention cannot be withheld from some tiers for a meaningful period for ethical or practical reasons.
Strengths & limitations
- Demonstrates experimental control without requiring a return-to-baseline phase, making it ethical when skill acquisition is irreversible.
- Each tier serves as an independent replication, strengthening the case for a functional relation.
- Applicable across diverse contexts: different participants, behaviors, or settings can serve as tiers.
- Well-accepted in applied behavior analysis, special education, and clinical psychology literatures.
- Produces rich, continuous behavioral data that reveal the trajectory and immediacy of intervention effects.
- Requires at least two (preferably three or more) functionally independent tiers; a design with only two tiers offers weaker experimental control.
- Data collection must be continuous across all tiers simultaneously from the start, which is resource-intensive.
- Generalization of findings across participants or settings is limited by the small, often non-random samples inherent in single-subject research.
- If tiers are not truly independent, behavior may change in untreated tiers (multiple baseline covariation), threatening internal validity.
Frequently asked
How many tiers do I need?
A minimum of two tiers is required, but three or more tiers are strongly recommended. With only two tiers the design provides a single replication, which is a relatively weak demonstration of experimental control. Most methodologists and journal reviewers consider three tiers the practical minimum for a credible functional relation claim.
What counts as a 'tier' — can I mix behaviors, participants, and settings?
Each study uses one type of tier for conceptual clarity. A multiple baseline across behaviors uses the same participant in the same setting but targets different behaviors. A multiple baseline across participants uses the same behavior and setting but different individuals. A multiple baseline across settings uses the same participant and behavior in different settings. Mixing tier types within a single study is non-standard and complicates interpretation.
How do I know when to advance to the next tier?
The standard criterion is that the tier currently receiving the intervention shows a clear, stable change in level and/or trend relative to its baseline — and that this change appears unlikely to reverse. Common conventions include three to five consecutive data points in the intervention phase that demonstrate the expected direction of change with low variability. There is no single universal rule; the criterion should be pre-specified and reported.
Is the multiple baseline design suitable for group data?
No. The multiple baseline design is a single-subject (single-case) design. Each tier is analyzed individually, and the logic of replication is based on within-subject comparison over time, not between-group comparison. If you have a sample large enough for group-level inference, a randomized controlled trial or quasi-experimental design is more appropriate.
Can I use statistical analysis instead of visual analysis?
Visual analysis is the conventional and primary method in single-case research. Effect size indices such as Tau-U, non-overlap of all pairs (NAP), or the percentage of non-overlapping data (PND) are widely used as supplements and for meta-analytic purposes, but they do not replace careful visual inspection of graphed data for phase-level interpretation.
Sources
- Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1(1), 91–97. DOI: 10.1901/jaba.1968.1-91 ↗
- Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). Applied Behavior Analysis (3rd ed.). Pearson. ISBN: 978-0134752556
How to cite this page
ScholarGate. (2026, June 3). Multiple Baseline Single-Subject Experimental Design. ScholarGate. https://scholargate.app/en/experimental-design/multiple-baseline-design
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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