testCompareR: an R package to compare two binary diagnostic tests using paired data

  • Kyle J. Wilson
  • , José A. Roldán-Nofuentes
  • , Marc Y.R. Henrion

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Background: Binary diagnostic tests are commonly used in medicine to answer a question about a patient’s clinical status, most commonly, do they or do they not have some disease. Recent advances in statistical methodologies for performing inferential statistics to compare commonly used test metrics for two diagnostic tests have not yet been implemented in a robust statistical package. Methods: Up-to-date statistical methods to compare the test metrics achieved by two binary diagnostic tests are implemented in the new R package testCompareR. The output and efficiency of testCompareR is compared to the only other available package which performs this function, DTComPair, as well as an open-source program, compbdt, using a motivating example. Results: testCompareR achieves similar results to DTComPair using statistical methods with improved coverage and asymptotic performance. Further, testCompareR is faster than the currently available package and requires fewer pre-processing steps in order to produce accurate results. Conclusions: testCompareR provides a new tool to compare the test metrics for two binary diagnostic tests compared with the gold standard. This tool allows flexible inputs, which minimises the need for data pre-processing, and operates in very few steps, so that it is easy to use even for those less experienced with R. testCompareR achieves results comparable to those computed by DTComPair, using optimised statistical methods and with improved computational efficiency.

Original languageEnglish
Article number351
JournalWellcome Open Research
Volume9
DOIs
StatePublished - 2024
Externally publishedYes

Keywords

  • R package
  • binary
  • compare
  • diagnostic test
  • dichotomous
  • paired data

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