A Priori Justification for Effect Measures in Single-Case Experimental Designs.

Area of Science:

• Behavioral Science
• Research Methodology
• Psychology

Background:

• Single-case experimental designs (SCED) involve complex data analysis.
• Numerous effect measures exist, but inappropriate selection can misrepresent intervention effectiveness.
• Lack of clear guidelines for effect measure selection and justification is a significant issue.

Purpose of the Study:

• To identify key dimensions for selecting and justifying effect measures in SCED prior to data collection.
• To develop a user-friendly flowchart to guide applied researchers in choosing appropriate effect measures.
• To prevent selective reporting of intervention effects and enhance study credibility.

Main Methods:

• Systematic identification of dimensions for effect measure selection and justification.
• Construction of a decision-tree flowchart based on identified dimensions.
• Illustration of the flowchart's application using a preregistered SCED protocol.

Main Results:

• Established dimensions for effect measure selection and justification in SCED.
• Developed a practical flowchart to aid researchers in this critical decision-making process.
• Demonstrated the utility of the flowchart in a real-world research scenario.

Conclusions:

• Implementing these guidelines and the flowchart can improve the rigor of SCED research.
• Transparent and justified effect measure selection reduces confirmation bias and enhances findings' credibility.
• This work provides the first reporting guidelines to justify effect measure choice before data collection in SCED.