47 citations · 227 across the 20 of their papers we have counts for
21 papers
1-truncated C-vine copula mixed models for network meta-analysis of multiple diagnostic tests
Aristidis K. Nikoloulopoulos
As meta-analysis of multiple diagnostic tests impacts clinical decision making and patient health, there is growing interest in statistical models that synthesize evidence from stu…
Efficient and feasible inference for high-dimensional normal copula regression models
Aristidis K. Nikoloulopoulos
The composite likelihood (CL) is amongst the computational methods used for the estimation of high-dimensional multivariate normal (MVN) copula models with discrete responses. Its…
Factor tree copula models for item response data
Sayed H. Kadhem, Aristidis K. Nikoloulopoulos
Factor copula models for item response data are more interpretable and fit better than (truncated) vine copula models when dependence can be explained through latent variables, but…
Bi-factor and second-order copula models for item response data
Sayed H. Kadhem, Aristidis K. Nikoloulopoulos
Bi-factor and second-order models based on copulas are proposed for item response data, where the items can be split into non-overlapping groups such that there is a homogeneous de…
A multinomial truncated D-vine copula mixed model for the joint meta-analysis of multiple diagnostic tests
Aristidis K. Nikoloulopoulos
There is an extensive literature on methods for meta-analysis of diagnostic studies, but it mainly focuses on a single test. However, the better understanding of a particular disea…
An one-factor copula mixed model for joint meta-analysis of multiple diagnostic tests
Aristidis K. Nikoloulopoulos
As the meta-analysis of more than one diagnostic tests can impact clinical decision making and patient health, there is an increasing body of research in models and methods for met…
The bivariate -finite normal mixture "blanket" copula
Aristidis K. Nikoloulopoulos
There exist many bivariate parametric copulas to model bivariate data with different dependence features. We propose a new bivariate parametric copula family that cannot only handl…
Factor copula models for mixed data
Sayed H. Kadhem, Aristidis K. Nikoloulopoulos
We develop factor copula models for analysing the dependence among mixed continuous and discrete responses. Factor copula models are canonical vine copulas that involve both observ…
A multinomial quadrivariate D-vine copula mixed model for meta-analysis of diagnostic studies in the presence of non-evaluable subjects
Aristidis K. Nikoloulopoulos
Diagnostic test accuracy studies observe the result of a gold standard procedure that defines the presence or absence of a disease and the result of a diagnostic test. They typical…
An extended trivariate vine copula mixed model for meta-analysis of diagnostic studies in the presence of non-evaluable outcomes
Aristidis K. Nikoloulopoulos
A recent paper proposed an extended trivariate generalized linear mixed model (TGLMM) for synthesis of diagnostic test accuracy studies in the presence of non-evaluable index test…
A D-vine copula mixed model for joint meta-analysis and comparison of diagnostic tests
Aristidis K. Nikoloulopoulos
For a particular disease there may be two diagnostic tests developed, where each of the tests is subject to several studies. A quadrivariate generalized linear mixed model (GLMM) h…
On composite likelihood in bivariate meta-analysis of diagnostic test accuracy studies
Aristidis K. Nikoloulopoulos
The composite likelihood (CL) is amongst the computational methods used for estimation of the generalized linear mixed model (GLMM) in the context of bivariate meta-analysis of dia…
A copula-based model for multivariate ordinal panel data: application to well-being composition
Aristidis K. Nikoloulopoulos, Emmanouil Mentzakis
A novel copula-based multivariate panel ordinal model is developed to estimate structural relations among components of well-being. Each ordinal time-series is modelled using a cop…
Coupling couples with copulas: analysis of assortative matching on risk attitude
Aristidis K. Nikoloulopoulos, Peter G. Moffatt
We investigate patterns of assortative matching on risk attitude, using self-reported (ordinal) data on risk attitudes for males and females within married couples, from the German…
Hybrid copula mixed models for combining case-control and cohort studies in meta-analysis of diagnostic tests
Aristidis K. Nikoloulopoulos
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 biostatisti…
Correlation structure and variable selection in generalized estimating equations via composite likelihood information criteria
Aristidis K. Nikoloulopoulos
The method of generalized estimating equations (GEE) is popular in the biostatistics literature for analyzing longitudinal binary and count data. It assumes a generalized linear mo…
Weighted scores method for longitudinal ordinal data
Aristidis K. Nikoloulopoulos
Extending generalized estimating equations (GEE) to ordinal response data requires a conversion of the ordinal response to a vector of binary category indicators. That leads to a r…
A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence
Aristidis K. Nikoloulopoulos
A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that is superior to the standard generalized linear m…
A mixed effect model for bivariate meta-analysis of diagnostic test accuracy studies using a copula representation of the random effects distribution
Aristidis K. Nikoloulopoulos
Diagnostic test accuracy studies typically report the number of true positives, false positives, true negatives and false negatives. There usually exists a negative association bet…
Efficient estimation of high-dimensional multivariate normal copula models with discrete spatial responses
Aristidis K. Nikoloulopoulos
The distributional transform (DT) is amongst the computational methods used for estimation of high-dimensional multivariate normal copula models with discrete responses. Its advant…
On the estimation of normal copula discrete regression models using the continuous extension and simulated likelihood
Aristidis K. Nikoloulopoulos
The continuous extension of a discrete random variable is amongst the computational methods used for estimation of multivariate normal copula-based models with discrete margins. It…