Which design combines multiple baseline, reversal, and/or alternating treatment tactics to compare the effects of two or more independent variables?

Which design combines multiple baseline, reversal, and/or alternating treatment tactics to compare the effects of two or more independent variables?

• A. Multielement Design
• B. Alternating Treatments Design
• C. Component Analysis
• D. Multiple Baseline Design

Answer: (C)

This item is about identifying which parts of a treatment package actually drive change by testing each component as a separate variable and watching how behavior changes when components are added, removed, or varied. In a component analysis, you compare two or more independent variables—the components themselves—by manipulating them within the same study. You might use baseline periods across components or settings and incorporate reversals or alternating treatments to observe the effects when a component is present versus absent, alone or in combination. This systematic isolation lets you determine which components are necessary or sufficient for the observed improvements. Other designs can compare different treatment conditions or demonstrate control across multiple baselines, but they aren’t as focused on dissecting a package into its active components and evaluating each one’s contribution. Component analysis is specifically aimed at figuring out which parts of the package actually produce the change.

This item is about identifying which parts of a treatment package actually drive change by testing each component as a separate variable and watching how behavior changes when components are added, removed, or varied. In a component analysis, you compare two or more independent variables—the components themselves—by manipulating them within the same study. You might use baseline periods across components or settings and incorporate reversals or alternating treatments to observe the effects when a component is present versus absent, alone or in combination. This systematic isolation lets you determine which components are necessary or sufficient for the observed improvements.

Other designs can compare different treatment conditions or demonstrate control across multiple baselines, but they aren’t as focused on dissecting a package into its active components and evaluating each one’s contribution. Component analysis is specifically aimed at figuring out which parts of the package actually produce the change.