title: Meta-analysis of diagnostic tests accounting for disease prevalence: a new model using trivariate copulas.
abstract: In real life and somewhat contrary to biostatistical textbook knowledge, sensitivity and specificity (and not only predictive values) of diagnostic tests can vary with the underlying prevalence of disease. In meta-analysis of diagnostic studies, accounting for this fact naturally leads to a trivariate expansion of the traditional bivariate logistic regression model with random study effects. In this paper, a new model is proposed using trivariate copulas and beta-binomial marginal distributions for sensitivity, specificity, and prevalence as an expansion of the bivariate model. Two different copulas are used, the trivariate Gaussian copula and a trivariate vine copula based on the bivariate Plackett copula. This model has a closed-form likelihood, so standard software (e.g., SAS PROC NLMIXED) can be used. The results of a simulation study have shown that the copula models perform at least as good but frequently better than the standard model. The methods are illustrated by two examples.
authors.affiliation: German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Duesseldorf, Institute for Biometry and Epidemiology, Duesseldorf, Germany.
authors.forename: A
authors.initials: A
authors.lastname: Hoyer
authors.forename: O
authors.initials: O
authors.lastname: Kuss
mesh_terms: D000465:Algorithms; D015982:Bias; D016010:Binomial Distribution; D003198:Computer Simulation; D005951:Glucose Tolerance Test; D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D009181:Mycoses / Q000097:blood*; D015995:Prevalence; D011509:Proteoglycans; D012107:Research Design; D012680:Sensitivity and Specificity; D012984:Software; D047071:beta-Glucans / Q000097:blood*
chemical_list: D011509:Proteoglycans; D047071:beta-Glucans; C010770:polysaccharide-K
keywords: beta-binomial distribution; copula; meta-analysis; prevalence; sensitivity; specificity