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 language | English |
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Pages (from-to) | 2540-2553 |
Number of pages | 14 |
Journal | Statistical Methods in Medical Research |
Volume | 27 |
Issue number | 8 |
Early online date | 21 Dec 2016 |
DOIs | |
Publication status | Published - 1 Aug 2018 |
Keywords
- Generalized linear mixed model
- composite likelihood
- maximum likelihood
- sensitivity/specificity/prevalnce
Profiles
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Aristidis K. Nikoloulopoulos
- School of Engineering, Mathematics and Physics - Associate Professor in Statistics
- Numerical Simulation, Statistics & Data Science - Member
Person: Research Group Member, Academic, Teaching & Research