Hybrid copula mixed models for combining case-control and cohort studies in meta-analysis of diagnostic tests

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Abstract

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.
Original languageEnglish
Pages (from-to)2540-2553
Number of pages14
JournalStatistical Methods in Medical Research
Volume27
Issue number8
Early online date21 Dec 2016
DOIs
Publication statusPublished - 1 Aug 2018

Keywords

  • Generalized linear mixed model
  • composite likelihood
  • maximum likelihood
  • sensitivity/specificity/prevalnce

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