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Unscaled Indices for Assessing Agreement of Functional Data.

Kaeum Choi1, Jeong Hoon Jang2

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|February 19, 2025
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Assessing medical device agreement is crucial. This study introduces new indices (total deviation index and coverage probability) to evaluate the reliability and reproducibility of functional data from multiple measurement methods.

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Area of Science:

  • Biostatistics
  • Medical Imaging Analysis
  • Health Technology Assessment

Background:

  • Adopting new medical devices necessitates rigorous validation of clinical measurement reliability and reproducibility.
  • Functional data generated by high-tech medical devices require robust methods for assessing agreement across different measurement techniques.

Purpose of the Study:

  • To establish validity and acceptability of modern high-tech medical devices generating functional data.
  • To introduce novel indices for assessing agreement of multiple functional data measured by different methods/technologies/raters on the same subjects.
  • To develop methods for delineating intramethod, intermethod, and total agreement trends over time.

Main Methods:

  • Introduction of unscaled indices: total deviation index (TDI) and coverage probability (CP), which are functions of time.
  • Development of scalar-valued TDI and CP indices summarizing agreement over the entire domain using weighted averages.
  • Utilizing a bivariate multilevel functional linear mixed effects model to express indices based on mean functions and variance components.
  • Employing bivariate multilevel functional principal component analysis for smooth index estimation via eigenanalyses of univariate covariance functions.

Main Results:

  • The proposed indices (TDI and CP) can delineate trends of intramethod, intermethod, and total agreement across time on the original measurement scale.
  • Scalar-valued indices provide a summary of agreement over the entire data domain.
  • The functional principal component analysis approach ensures efficient and scalable estimation.
  • Simulation studies confirmed the finite-sample properties of the proposed estimators.

Conclusions:

  • The developed indices and methods provide a rigorous framework for assessing the reliability and reproducibility of functional data from medical devices.
  • The approach is applicable to diverse high-tech medical imaging devices, such as those used in diuresis renography for kidney obstruction detection.
  • This work contributes to the evidence-based adoption of advanced medical technologies by ensuring measurement consistency and validity.