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Related Experiment Videos

Assessing intra, inter and total agreement with replicated readings.

Huiman X Barnhart1, Jingli Song, Michael J Haber

  • 1Department of Biostatistics and Bioinformatics, Duke Clinical Research Institute, Duke University, P.O. Box 17969, Durham, NC 27715, USA. huiman.barnhart@duke.edu

Statistics in Medicine
|December 1, 2004
PubMed
Summary

This study introduces new agreement indices, inter-CCC and total-CCC, for evaluating multiple readings from several methods in clinical studies. These indices allow simultaneous assessment of intra-method, inter-method, and total agreement for continuous measurements.

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Area of Science:

  • Biostatistics
  • Medical Imaging Analysis
  • Clinical Trial Methodology

Background:

  • Assessing agreement for continuous measurements is crucial in clinical studies.
  • Traditional methods often fail to distinguish between intra-method and inter-method agreement when multiple readings are available.
  • Existing indices like ICC and CCC can conflate total agreement with inter-method agreement.

Purpose of the Study:

  • To develop novel agreement indices for situations with replicated readings from multiple methods.
  • To introduce inter-method CCC (inter-CCC) and total CCC (total-CCC) for comprehensive agreement assessment.
  • To provide a framework for simultaneously evaluating intra-method, inter-method, and total agreement.

Main Methods:

  • Proposed new agreement indices: inter-CCC and total-CCC.

Related Experiment Videos

  • Utilized intra-class correlation coefficients (ICCs) for intra-method agreement assessment.
  • Employed a generalized estimating equations approach for estimation and inference.

    • Main Results:

    • Demonstrated that traditional indices often represent total agreement, not solely inter-method agreement.
    • Investigated the relationships between the proposed total-CCC, inter-CCC, and intra-method ICCs.
    • Simulation studies confirmed the performance of the proposed generalized estimating equations approach.

    Conclusions:

    • The new indices (inter-CCC, total-CCC) enable a more nuanced evaluation of agreement with multiple readings from diverse methods.
    • The generalized estimating equations approach provides a robust statistical framework for these complex agreement data.
    • The methodology is illustrated using data from a carotid stenosis screening study, highlighting its practical applicability.