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Agreement between visual inspection and objective analysis methods: A replication and extension.

Tessa Taylor1,2, Marc J Lanovaz3

  • 1University of Canterbury/Te Whare Wānanga o Waitaha.

Journal of Applied Behavior Analysis
|April 28, 2022
PubMed
Summary
This summary is machine-generated.

Objective methods for analyzing behavior data align with expert visual inspection. This study found high agreement between visual inspection, the conservative dual-criteria method, and a machine-learning algorithm, supporting their use in treatment decisions.

Keywords:
artificial intelligenceconservative dual criteriainterrater agreementmachine learningvisual inspection

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Area of Science:

  • Behavior Analysis
  • Single-Case Experimental Designs
  • Quantitative Research Methods

Background:

  • Behavior analysts traditionally use visual inspection of single-case designs for treatment decisions.
  • Visual inspection is subjective, necessitating objective supplemental methods.
  • The conservative dual-criteria method and machine learning algorithms are objective alternatives.

Purpose of the Study:

  • To replicate and extend previous research on agreement between visual inspection and objective methods.
  • To examine the agreement between visual inspection by multiple raters, the conservative dual-criteria method, and a support vector classifier.
  • To assess the consistency of objective methods with expert visual analysis in behavior analysis.

Main Methods:

  • Analysis of 198 AB graphs from clinical behavior analysis data.
  • Comparison of visual inspection by five experienced raters.
  • Evaluation of agreement with the conservative dual-criteria method.
  • Assessment of agreement with a support vector classifier (machine learning algorithm).

Main Results:

  • High average agreement was observed between the three methods.
  • Mean interrater agreement among visual inspectors was 84%.
  • Raters agreed with the conservative dual-criteria method on 84% of graphs.
  • Raters agreed with the support vector classifier on 85% of graphs.

Conclusions:

  • Both the conservative dual-criteria method and the support vector classifier demonstrate high agreement with visual inspection.
  • Objective methods provide consistent results comparable to subjective visual analysis.
  • These findings support the potential future adoption of objective methods in behavior analysis for treatment decisions.