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An R-Based Landscape Validation of a Competing Risk Model

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Published on: September 16, 2022

Compbdt: an R program to compare two binary diagnostic tests subject to a paired design.

J A Roldán-Nofuentes¹

¹Department of Statistics (Biostatistics), School of Medicine, University of Granada, Avenida de la Investigación 11, 18016, Granada, Spain. jaroldan@ugr.es.

BMC Medical Research Methodology

|June 7, 2020

Summary

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.

Keywords:

Binary diagnostic test Likelihood ratios Paired design Predictive values Sensitivity and specificity

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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.