A graph that depicts multiple baseline across participants shows intervention being introduced at different times (staggered baselines) across two or more participants. Each participant's baseline data is initially collected independently, and the intervention phase starts sequentially, not simultaneously, for each participant. This design demonstrates the effect of the intervention across multiple individuals by comparing the timing and effects. Key characteristics of a multiple baseline across participants graph:
- Separate panels or lines for each participant.
- Baseline phases with data points that vary in length across participants.
- Intervention phases begin at different times for each participant, creating a "staggered" pattern.
- Only one phase change (baseline to treatment) per participant.
- The intervention effect is verified by changes only occurring after intervention starts, ruling out external variables.
This contrasts with multiple baseline across behaviors or settings, where the intervention is staggered across different behaviors or environments but within the same participant. The explanation and example visualization are usually presented with three or more separate graphs or panels vertically, each representing a different participant, showing the timeline and phase changes distinctly. This depiction is supported by behavior analysis literature and detailed guidelines on the multiple baseline design.
