Restricted accessEditorialFirst published online 2016-4
Comment on ‘A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence’ by Aristidis K Nikoloulopoulos
Nikoloulopoulos AK. A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence. Stat Meth Med Res. Epub ahead of print 2015. DOI: 10.1177/0962280215596769.
2.
HoyerAKussO. Statistical methods for meta-analysis of diagnostic tests accounting for prevalence – a new model using trivariate copulas. Stat Med2015; 34: 1912–1924.
3.
Nikoloulopoulos A. A mixed effect model for bivariate meta-analysis of diagnostic test accuracy studies using a copula representation of the random effects distribution. Stat Med. Epub ahead of print 2015. DOI: 10.1002/sim.6595.
4.
ChuHNieLColeSR. Meta-analysis of diagnostic accuracy studies accounting for disease prevalence: alternative parameterizations and model selection. Stat Med2009; 28: 2384–2399.
5.
NelsenRB. An introduction to copulas, New York, NY: Springer, 2006.
6.
SklarA. Fonctions de répartition à n dimensions et leurs marges. Publications de l’Institut de Statistique de L’Université de Paris1959; 8: 229–231.
7.
KarageorgopoulosDEVouloumanouEKNtzioraF. β-D-Glucan assay for the diagnosis of invasive fungal infections: a meta-analysis. Clin Infect Dis2011; 52: 750–770.
8.
MenkeJ. Bivariate random-effects meta-analysis of sensitivity and specificity with SAS PROC GLIMMIX. Meth Inform Med2010; 49: 54–62, 62–64–54–62, 62–64.