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Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

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Sample size determination for comparing accuracies between two diagnostic tests under a paired design.

Yi-Ting Hwang¹, Nan-Cheng Su¹

¹Department of Statistics, National Taipei University, New Taipei City, Taiwan.

Biometrical Journal. Biometrische Zeitschrift

|April 16, 2022

Summary

This study provides new nonparametric estimators for the variance and covariance of two area under the receiver operating characteristic curve (AUC) estimators. These are crucial for determining sample sizes in paired diagnostic test accuracy studies.

Keywords:

AUC ROC curve binormal model diagnostic test paired sample

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Area of Science:

Biostatistics
Medical Diagnostics
Statistical Modeling

Background:

Accurate diagnostic tests are crucial for timely disease detection.
Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC) are standard metrics for assessing diagnostic accuracy.
Sample size determination for paired diagnostic studies requires variance and covariance of AUC estimators.

Purpose of the Study:

To derive nonparametric estimators for the variance and covariance of two AUC estimators in paired designs.
To develop a sample size formula for paired diagnostic accuracy studies using these estimators.
To provide numerical results for various scenarios due to the lack of closed-form solutions.

Main Methods:

Derivation of nonparametric estimators for variance and covariance of two AUC estimators.
Development of a sample size formula for paired data based on these estimators.
Numerical simulations to evaluate performance under different conditions.

Main Results:

Nonparametric estimators for the variance and covariance of two AUC estimators were successfully derived.
A novel sample size formula for paired designs was established.
Numerical results illustrate the application and behavior of the formula across various scenarios.

Conclusions:

The derived estimators and sample size formula are valuable for planning paired diagnostic accuracy studies.
Accurate sample size calculation enhances the reliability and efficiency of diagnostic test evaluations.
The findings contribute to the statistical methodology for comparing diagnostic tests in paired settings.