Introduction
In the ever-evolving field of applied behavior analysis, multiple-baseline designs have become the cornerstone for single-case design (SCD) research. They are extensively utilized across various disciplines, from psychology to education. However, understanding the intricacies of these designs is crucial for practitioners who aim to enhance their research skills and ensure the validity of their findings.
Understanding Multiple-Baseline Designs
Multiple-baseline designs are experimental frameworks that evaluate causal relationships through baseline-treatment comparisons. These designs are divided into two types: concurrent and nonconcurrent. While concurrent designs synchronize tiers in real time, nonconcurrent designs allow for flexibility, as tiers do not need to be synchronized. Despite the prevalence of concurrent designs, nonconcurrent designs offer significant advantages, particularly in applied settings where simultaneous data collection is challenging.
Addressing Threats to Internal Validity
The primary goal of multiple-baseline designs is to control for threats to internal validity, which can compromise the integrity of research findings. Three major threats are:
- Maturation: Changes in behavior due to natural growth or environmental interactions over time.
- Testing and Session Experience: Behavioral changes resulting from repeated exposure to testing conditions.
- Coincidental Events (History): External events coinciding with the introduction of the independent variable.
Both concurrent and nonconcurrent designs effectively address these threats, but nonconcurrent designs offer unique advantages by allowing for longer lags between phase changes, thus providing stronger control over coincidental events.
Recommendations for Practitioners
Practitioners can enhance their research by implementing the following recommendations:
- Embrace nonconcurrent designs when simultaneous data collection is impractical, as they offer robust control over internal validity threats.
- Ensure sufficient lag between phase changes in terms of days, sessions, and calendar dates to effectively control for maturation, testing, and coincidental events.
- Focus on replicated within-tier comparisons to strengthen the evidence of treatment effects and rule out alternative explanations.
- Report the number of days, sessions, and calendar dates in each phase to provide a comprehensive evaluation of internal validity.
Conclusion
By understanding and implementing these strategies, practitioners can significantly enhance the rigor of their research designs. Nonconcurrent multiple-baseline designs, when used effectively, can provide strong evidence for causal relationships and support the development of evidence-based practices.
To read the original research paper, please follow this link: Threats to Internal Validity in Multiple-Baseline Design Variations.
