School of Computing Sciences, University of East Anglia, Norwich, UK.
Stat Methods Med Res. 2018 Aug;27(8):2540-2553. doi: 10.1177/0962280216682376. Epub 2016 Dec 21.
Copula mixed models for trivariate (or bivariate) meta-analysis of diagnostic test accuracy studies accounting (or not) for disease prevalence have been proposed in the biostatistics literature to synthesize information. However, many systematic reviews often include case-control and cohort studies, so one can either focus on the bivariate meta-analysis of the case-control studies or the trivariate meta-analysis of the cohort studies, as only the latter contains information on disease prevalence. In order to remedy this situation of wasting data we propose a hybrid copula mixed model via a combination of the bivariate and trivariate copula mixed model for the data from the case-control studies and cohort studies, respectively. Hence, this hybrid model can account for study design and also due to its generality can deal with dependence in the joint tails. We apply the proposed hybrid copula mixed model to a review of the performance of contemporary diagnostic imaging modalities for detecting metastases in patients with melanoma.
在生物统计学文献中,已经提出了用于对诊断测试准确性研究进行三重(或二元)荟萃分析的 Copula 混合模型,这些研究考虑(或不考虑)疾病流行率,以综合信息。然而,许多系统评价通常包括病例对照研究和队列研究,因此,人们可以专注于病例对照研究的二元荟萃分析,或者专注于队列研究的三重荟萃分析,因为只有后者包含有关疾病流行率的信息。为了弥补这种浪费数据的情况,我们提出了一种混合 Copula 混合模型,通过将二元和三重 Copula 混合模型分别结合用于病例对照研究和队列研究的数据。因此,该混合模型可以考虑研究设计,并且由于其通用性,可以处理联合尾部的相关性。我们将提出的混合 Copula 混合模型应用于对当代诊断成像方式在检测黑色素瘤患者转移中的性能的综述。