Single-Subject Experimental Design
Also known as: SSED, single-case experimental design, n-of-1 design, intrasubject replication design
Single-subject experimental design (SSED) establishes experimental control by repeatedly measuring one individual (or a small number of individuals) across baseline and intervention phases, using the participant as their own control. Instead of comparing groups, it compares the participant's own behavior across conditions over time. Widely used in applied behavior analysis, special education, rehabilitation, and clinical psychology, SSED allows causal inference from small or unique samples where group designs are impractical.
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When to use it
Use SSED when you need experimental evidence about the effect of an intervention on a specific individual or a very small number of individuals — for example, a student with a rare disability, a patient with a unique clinical profile, or a participant pool too small for group designs. It is appropriate when ethical or logistical constraints prevent withholding treatment from a control group, and when frequent repeated measurement of a well-defined behavior over time is feasible. Do NOT use SSED when the research question concerns population-level prevalence or average effects, when the target behavior cannot be measured repeatedly and objectively, when carry-over or irreversible treatment effects would prevent a meaningful return to baseline, or when the goal is norm-referenced comparison rather than individual-level functional analysis.
Strengths & limitations
- Allows causal inference from very small or unique samples where group designs are impossible or unethical.
- The participant serves as their own control, eliminating between-subject variability and making individual change transparent.
- Continuously collected data reveal the temporal dynamics of behavior change — not just pre- and post-snapshots.
- Flexible: multiple design variants (AB, ABA, ABAB, multiple baseline, alternating treatments) accommodate diverse research questions and ethical constraints.
- Replication across participants, settings, and behaviors builds a cumulative evidence base analogous to meta-analytic convergence.
- Findings are specific to the individual(s) studied; statistical generalization to a population is not warranted from a single study.
- Requires frequent, repeated, objective measurement of a clearly operationalized target behavior — feasible for overt behaviors, harder for internal states.
- Reversal designs are inappropriate when the intervention teaches a skill that cannot be unlearned, making the return-to-baseline phase illogical or unethical.
- Visual analysis is inherently subjective; interrater agreement on phase-change conclusions is not always high, and quantitative effect-size supplements are underused.
- Carryover effects between rapidly alternating conditions (in alternating-treatments designs) can confound results.
Frequently asked
Is single-subject design 'real' experimental research, or is it just a case study?
It is experimental. A case study describes what happened; a single-subject experimental design actively manipulates an independent variable and controls for confounds through replication of phase changes within the same participant. The logic of causal inference differs from group designs (it rests on intrasubject rather than intersubject replication) but is nonetheless rigorous when design conditions are met.
How many data points do I need in each phase?
The general guideline is a minimum of three to five data points per phase, but more are always preferable. The criterion is not a fixed number but stability: collect data until the pattern is predictable (stable level, clear trend, or acceptable variability) before changing phases. Rushing to introduce the intervention after only one or two baseline points undermines causal interpretation.
When should I use a multiple-baseline design instead of a reversal (ABA/ABAB) design?
Use a multiple-baseline design when the intervention effect is likely to be irreversible (e.g., skill acquisition), when withdrawing treatment would be unethical, or when a reversal would undo genuine therapeutic gains. A reversal design is most appropriate when the target behavior is expected to return toward baseline once the intervention is removed — typically operant behaviors maintained by environmental contingencies rather than learned skills.
Can I use statistics with single-subject data, or is visual analysis enough?
Visual analysis is the primary and traditional method, but quantitative supplements are encouraged. Nonoverlap statistics such as Nonoverlap of All Pairs (NAP), Tau-U, or Percentage of Nonoverlapping Data (PND) provide an objective effect-size index and aid communication with audiences unfamiliar with time-series graphs. Multilevel modeling and randomization tests are also applicable when the data and design warrant them.
How do I establish external validity from a study with only one or a few participants?
External validity in SSED is built through systematic replication across studies — your own replication across multiple participants within the same study (direct replication) and subsequent studies across different settings, populations, and researchers (systematic replication). A single study does not establish external validity; a body of replicated studies does. This is analogous to the role of meta-analysis for group-design literatures.
Sources
- Kazdin, A. E. (1982). Single-Case Research Designs: Methods for Clinical and Applied Settings. Oxford University Press. ISBN: 978-0195030440
- Sidman, M. (1960). Tactics of Scientific Research: Evaluating Experimental Data in Psychology. Basic Books. link ↗
How to cite this page
ScholarGate. (2026, June 3). Single-Subject Experimental Design. ScholarGate. https://scholargate.app/en/experimental-design/single-subject-experimental-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.
- AB DesignExperimental design↔ compare
- ABA DesignExperimental design↔ compare
- ABAB designExperimental design↔ compare
- Case StudyQualitative↔ compare
- Multiple Baseline DesignExperimental design↔ compare
- Pretest-Posttest Experimental DesignExperimental design↔ compare