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Published on: September 16, 2022
Compbdt: an R program to compare two binary diagnostic tests subject to a paired design
1Department of Statistics (Biostatistics), School of Medicine, University of Granada, Avenida de la Investigación 11, 18016, Granada, Spain. jaroldan@ugr.es.
This study introduces the "compbdt" R program for comparing two binary diagnostic tests using paired designs. It aids researchers in evaluating test performance, including sensitivity, specificity, and likelihood ratios, with robust statistical methods.
Area of Science:
- Clinical Medicine
- Biostatistics
- Medical Diagnostics
Background:
- Comparing binary diagnostic tests is crucial in clinical medicine.
- Paired designs are common for this comparison, involving applying two tests to individuals with known disease status.
- This article introduces an R program for analyzing paired diagnostic test data.
Purpose of the Study:
- To present an R program, "compbdt", for comparing parameters of two binary diagnostic tests under a paired design.
- To provide researchers with a tool for comprehensive analysis and interpretation of diagnostic test performance.
Main Methods:
- The "compbdt" program estimates sensitivity, specificity, likelihood ratios, and predictive values.
- It utilizes confidence intervals with optimal asymptotic performance and global hypothesis tests for simultaneous comparison.
- Holm's multiple comparison method is applied to investigate significant findings.
Main Results:
- The program calculates optimal confidence intervals for parameter differences or ratios.
- It estimates the probability of type II error or statistical power based on observed data.
- The "compbdt" program has been successfully applied to coronary artery disease diagnosis.
Conclusions:
- The "compbdt" program offers an easy-to-use solution for comparing key parameters of binary diagnostic tests in paired designs.
- It provides essential results for straightforward interpretation by researchers.
- The program is available as supplementary material.
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