Probability and Visual Aids for Assessing Intervention Effectiveness in Single-Case Designs: A Field Test.

Area of Science:

• Behavioral Sciences
• Quantitative Psychology
• Research Methodology

Background:

• Single-case data analysis traditionally relies on visual inspection.
• Objective quantitative methods are needed to complement visual analysis and ensure consistency.
• The convergence of different quantitative procedures in identifying intervention effects remains unclear.

Purpose of the Study:

• To compare the agreement between two quantitative procedures for single-case data analysis.
• To assess the convergence in identifying intervention effect magnitude using these methods.
• To evaluate the utility of a probability-based approach for effect size interpretation.

Main Methods:

• A visual aid procedure fitting a split-middle trend with data variability was employed.
• A probability-based procedure converting various metrics into comparable probabilities was utilized.
• These procedures were applied to data from studies within a recent meta-analysis.

Main Results:

• Both quantitative procedures showed considerable agreement with computed indices and with each other.
• Agreement with visual analysis was less pronounced compared to the agreement between the two quantitative methods.
• The probability-based approach demonstrated effectiveness in distinguishing smaller from larger effects and standardizing metric labels.

Conclusions:

• The two quantitative procedures demonstrate substantial concordance in analyzing single-case intervention effects.
• The probability-based method offers a robust tool for effect size interpretation and metric standardization.
• User-friendly R code is provided to facilitate the adoption of these analytical tools.