Blocked Multiple Baseline Design

A blocked multiple baseline design is a single-subject experimental approach that combines the logic of the multiple baseline design with blocking — the systematic grouping of participants, behaviors, or settings into matched sets — to reduce extraneous variability and strengthen causal inference. The intervention is introduced in a staggered sequence across baselines within each block, demonstrating experimental control through replication within and across blocks.