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Bayesian Gower agreement for categorical data.

John Hughes1

  • 1Lehigh University, Bethlehem, PA, 18015, USA. drjphughesjr@gmail.com.

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This summary is machine-generated.

This study introduces novel Gower-distance-based methods for measuring inter-rater agreement in nominal and ordinal data. These intuitive techniques easily identify influential units or coders and are supported by an open-source R package.

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Area of Science:

  • Statistics
  • Data Analysis
  • Measurement Science

Background:

  • Accurate measurement of agreement is crucial in various fields, including medical research and diagnostics.
  • Existing methods for assessing agreement in nominal and ordinal data can be complex or limited in scope.
  • Identifying influential units or coders is essential for data quality assessment.

Purpose of the Study:

  • To develop and present novel, simple, and intuitive methods for measuring agreement in nominal and ordinal data.
  • To extend these methods to accommodate both one-way and two-way random sampling designs.
  • To provide a robust approach to Bayesian inference for agreement measures.

Main Methods:

  • Utilizing Gower-type distances for calculating agreement scores.
  • Developing Bayesian inference approaches for one-way and two-way random sampling designs.
  • Applying proposed methods to simulated and real-world datasets, including radiological and psychiatric studies.

Main Results:

  • The proposed Gower-distance-based methods are demonstrated to be simple, intuitive, and computationally efficient.
  • The methods facilitate the straightforward identification of influential units and/or coders.
  • Bayesian inference frameworks are successfully developed for both one-way and two-way designs.
  • The study suggests Gaussian mutual information as a potentially more useful agreement scale.

Conclusions:

  • The presented methods offer a flexible and accessible approach to quantifying inter-rater agreement.
  • The open-source R package 'goweragreement' supports the practical application of these statistical techniques.
  • Further research into alternative agreement scales, such as Gaussian mutual information, is warranted.