Which of the following is NOT a small-N design?
interrupted time-series design
multiple-baseline design
reversal design
stable-baseline design
The correct answer and explanation is:
The correct answer is interrupted time-series design.
An interrupted time-series design is not considered a small-N design because it typically involves large amounts of data collected over time. This design is usually applied to evaluate the impact of an intervention or event by examining changes in a time-series dataset before and after the intervention. It can include multiple subjects or units (such as individuals, organizations, or communities), and as such, it is not restricted to a small number of participants.
In contrast, small-N designs are characterized by focusing on a limited number of subjects or cases, often just one or a few. These designs allow researchers to study individual behavior in-depth and often use repeated measurements to evaluate the effects of interventions. The key types of small-N designs include:
- Multiple-baseline design: This design involves introducing an intervention at different times across multiple subjects, settings, or behaviors. The goal is to observe changes in behavior as a result of the intervention while maintaining control over other variables.
- Reversal design: In this design, an intervention is introduced and then withdrawn, with the researcher observing how behavior changes during both phases. This type of design relies on the ability to reverse the effect of the intervention, and it typically uses one participant or a few participants.
- Stable-baseline design: This design involves observing a participant’s behavior over a period of time before the intervention is introduced to establish a baseline. The goal is to demonstrate that any changes in behavior after the intervention are due to the intervention itself rather than other factors.
These small-N designs are ideal for cases where individual variation is significant, and they help focus on understanding how specific interventions affect a few individuals in depth, often in clinical, educational, or behavioral research settings.