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

Q1 Medicine Wellcome Open Research Pub Date : 2024-11-26 eCollection Date: 2024-01-01 DOI:10.12688/wellcomeopenres.22411.3
Kyle J Wilson, José A Roldán-Nofuentes, Marc Y R Henrion
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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 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.

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testCompareR:使用配对数据比较两个二元诊断检测的 R 软件包。
背景:医学中常用二元诊断检测来回答有关病人临床状态的问题,最常见的是病人是否患有某种疾病。最近在统计方法学方面取得的进展,可用于比较两种诊断测试的常用测试指标:新的 R 软件包 testCompareR 采用了最新的统计方法来比较两种二元诊断检测的检验指标。结果:testCompareR 使用统计方法获得了与 DTComPair 相似的结果,覆盖率和渐近性能都有所提高。此外,testCompareR 比目前可用的软件包速度更快,而且需要更少的预处理步骤就能生成准确的结果。结论:testCompareR 提供了一种新工具,用于比较两个二元诊断检测与黄金标准的测试指标。该工具允许灵活的输入,从而最大限度地减少了数据预处理的需要,而且操作步骤很少,因此即使是对 R 经验不足的人也很容易使用。testCompareR 使用优化的统计方法和更高的计算效率得出了与 DTComPair 计算结果相当的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Wellcome Open Research
Wellcome Open Research Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
5.50
自引率
0.00%
发文量
426
审稿时长
1 weeks
期刊介绍: Wellcome Open Research publishes scholarly articles reporting any basic scientific, translational and clinical research that has been funded (or co-funded) by Wellcome. Each publication must have at least one author who has been, or still is, a recipient of a Wellcome grant. Articles must be original (not duplications). All research, including clinical trials, systematic reviews, software tools, method articles, and many others, is welcome and will be published irrespective of the perceived level of interest or novelty; confirmatory and negative results, as well as null studies are all suitable. See the full list of article types here. All articles are published using a fully transparent, author-driven model: the authors are solely responsible for the content of their article. Invited peer review takes place openly after publication, and the authors play a crucial role in ensuring that the article is peer-reviewed by independent experts in a timely manner. Articles that pass peer review will be indexed in PubMed and elsewhere. Wellcome Open Research is an Open Research platform: all articles are published open access; the publishing and peer-review processes are fully transparent; and authors are asked to include detailed descriptions of methods and to provide full and easy access to source data underlying the results to improve reproducibility.
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