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A parametric comparison of diagnostic accuracy with three ordinal diagnostic groups
Chengjie Xiong1, Gerald van Belle, J Philip Miller
1Division of Biostatistics, Washington University in St. Louis, St. Louis, MO 63110, USA. chengjie@wubios.wustl.edu
Biometrical Journal. Biometrische Zeitschrift
|September 1, 2007
Summary
This study introduces statistical methods to compare diagnostic accuracy using Receiver Operating Characteristic (ROC) surfaces for multiple tests with three ordinal diagnostic groups. The methods assess if diagnostic accuracy is equivalent across tests, aiding in medical diagnostic study analysis.
Area of Science:
- Biostatistics
- Medical Diagnostics
- Machine Learning
Background:
- Medical diagnostic studies often involve three ordinal diagnostic groups.
- Diagnostic accuracy is frequently summarized by the volume under a Receiver Operating Characteristic (ROC) surface.
- Comparing diagnostic accuracy across multiple tests with ordinal groups requires robust statistical methods.
Purpose of the Study:
- To develop statistical methods for comparing diagnostic accuracy across multiple diagnostic tests with three ordinal groups.
- To provide statistical tests for assessing the equivalence of diagnostic accuracy measured by ROC surface volume.
- To propose confidence intervals for the difference in ROC surface volumes between two diagnostic tests.
Main Methods:
- Utilizing the volume under the ROC surface to quantify diagnostic accuracy for three ordinal diagnostic groups.
- Assuming multivariate normal distribution for diagnostic tests within each diagnostic group.
- Deriving asymptotic variance and covariance for maximum likelihood estimates of ROC surface volumes.
- Proposing statistical tests and confidence intervals for comparing diagnostic accuracy.
Main Results:
- The study provides asymptotic variances and covariances for maximum likelihood estimates of ROC surface volumes.
- Statistical tests are proposed to determine if diagnostic accuracy is the same across multiple tests.
- A confidence interval estimate for the difference between two ROC surface volumes is presented.
Conclusions:
- The proposed methodology offers a framework for statistically comparing diagnostic accuracy in multi-test scenarios with ordinal groups.
- The approach relies on the assumption of multivariate normality, which may limit robustness if violated.
- The methods were applied to compare Alzheimer's disease diagnostic accuracy using neuropsychological tests.
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