Unit of Cancer Epidemiology, Belgian Cancer Centre, Brussels, Belgium.
Res Synth Methods. 2023 May;14(3):544-562. doi: 10.1002/jrsm.1634. Epub 2023 Apr 18.
We developed metadta, a flexible, robust, and user-friendly statistical procedure that fuses established and innovative statistical methods for meta-analysis, meta-regression, and network meta-analysis of diagnostic test accuracy studies in Stata. Using data from published meta-analyses, we validate metadta by comparing and contrasting its features and output to popular procedures dedicated to the meta-analysis of diagnostic test accuracy studies; (midas [Stata], metandi [Stata], metaDTA [web application], mada [R], and MetaDAS [SAS]). We also demonstrate how to perform network meta-analysis with metadta, for which no alternative procedure is dedicated to network meta-analysis of diagnostic test accuracy data in the frequentist framework. metadta generated consistent estimates in simple and complex diagnostic test accuracy data sets. We expect its availability to stimulate better statistical practice in the evidence synthesis of diagnostic test accuracy studies.
我们开发了 metadta，这是一种灵活、强大且用户友好的统计程序，可融合已建立和创新的统计方法，用于对诊断测试准确性研究进行荟萃分析、荟萃回归和网络荟萃分析。使用来自已发表的荟萃分析的数据，我们通过比较和对比其功能和输出，来验证 metadta 与专门用于诊断测试准确性研究荟萃分析的流行程序（midas [Stata]、metandi [Stata]、metaDTA [网络应用程序]、mada [R] 和 MetaDAS [SAS]）的异同。我们还展示了如何使用 metadta 进行网络荟萃分析，因为在经典框架中，没有专门针对诊断测试准确性数据的网络荟萃分析的替代程序。metadta 在简单和复杂的诊断测试准确性数据集上生成了一致的估计值。我们希望其可用性能够促进诊断测试准确性研究证据综合中更好的统计实践。
