D6 Critique and interpret data from single-case experimental designs

D.6 Critique and interpret data from single-case experimental designs.

Critiquing and interpreting data from single-case experimental designs involves analyzing the data collected on an individual participant over time to assess the effects of an intervention. This includes looking at trends, variability, and patterns in the data to determine if the intervention caused meaningful behavior change.

Example: In a single-case design, you might implement a behavior intervention to reduce a child’s outbursts and track the frequency of outbursts over several weeks. After analyzing the data, you notice a clear decrease in outbursts during the intervention phase compared to the baseline (pre-intervention) phase. You then critique the data by looking at factors like variability (whether behavior fluctuated) and consistency in reducing outbursts across different settings (e.g., home and school). Based on these observations, you interpret that the intervention successfully reduced the target behavior.

D. Experimental Design

D.1. Distinguish between dependent and independent variables.

D.2. Distinguish between internal and external validity.

D.3. Identify threats to internal validity (e.g., history, maturation).

D.4. Identify the defining features of single-case experimental designs (e.g., individuals serve as their own controls, repeated measures, prediction, verification, replication).

D.5. Identify the relative strengths of single-case experimental designs and group designs.

D.6. Critique and interpret data from single-case experimental designs.

D.7. Distinguish among reversal, multiple-baseline, multielement, and changing-criterion designs.

D.8. Identify rationales for conducting comparative, component, and parametric analyses.

D.9. Apply single-case experimental designs.