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CopulaREMADA (version 1.5)

Copula Mixed Models for Multivariate Meta-Analysis of Diagnostic Test Accuracy Studies

Description

The bivariate copula mixed model for meta-analysis of diagnostic test accuracy studies in Nikoloulopoulos (2015) . The vine copula mixed model for meta-analysis of diagnostic test accuracy studies accounting for disease prevalence in Nikoloulopoulos (2017) and also accounting for non-evaluable subjects in Nikoloulopoulos (2020) . The hybrid vine copula mixed model for meta-analysis of diagnostic test accuracy case-control and cohort studies in Nikoloulopoulos (2018) . The D-vine copula mixed model for meta-analysis and comparison of two diagnostic tests in Nikoloulopoulos (2019) . The multinomial quadrivariate D-vine copula mixed model for meta-analysis of diagnostic tests with non-evaluable subjects in Nikoloulopoulos (2020) . The one-factor copula mixed model for joint meta-analysis of multiple diagnostic tests (2020) .

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Version

Install

install.packages('CopulaREMADA')

Monthly Downloads

622

Version

1.5

License

GPL (>= 2.10)

Maintainer

Aristidis Nikoloulopoulos

Last Published

February 9th, 2022

Functions in CopulaREMADA (1.5)

FactorCopulaREMADA

Maximum likelihood estimation of 1-factor copula mixed models for joint meta-analysis of \(T\) diagnostic tests
MK2016

The coronary CT angiography data in Menke and Kowalski (2016).
MRI

The magnetic resonance imaging data
SROC

Summary receiver operating characteristic curves for copula mixed effect models for bivariate meta-analysis of diagnostic test accuracy studies
CopulaREMADA-package

Copula Mixed Models for Multivariate Meta-Analysis of Diagnostic Test Accuracy Studies
OGT

The orale glucose tolerance data
VineCopulaREMADA

Maximum likelhood estimation for (truncated) vine copula mixed models for diagnostic test accurracy studies accounting for disease prevalence and non-evaluable outcomes
mgrid

A list containing four-dimensional arrays
LAG

The lymphangiography data
CT

The computing tomography data
CopulaREMADA

Maximum likelhood estimation for copula mixed models for diagnostic test accurracy studies
cvinesim

Simulation from a trivariate C-vine copula
rCopulaREMADA

Simulation from copula mixed models for diagnostic test accuaracy studies
quadVineCopulaREMADA

Maximum likelihood estimation of quadrivariate D-vine copula mixed models for joint meta-analysis and comparison of two diagnostic tests
vine.vuong

Vuong's test for the comparison of non-nested vine copula mixed models for diagnostic test accuaracy studies
rFactorCopulaREMADA

Simulation from 1-factor copula mixed models for joint meta-analysis of \(T\) diagnostic tests
coronary

The coronary CT angiography data
betaDG

The beta-D-Glucan-data
rVineCopulaREMADA

Simulation from trivariate vine copula mixed models for diagnostic test accuaracy studies accounting for disease prevalence and non-evaluable results
mutinomVineCopulaREMADA

Maximum likelhood estimation for multinomial quadrivariate (truncated) D-vine copula mixed models for diagnostic test accurracy studies accounting for non-evaluable outcomes
arthritis

The rheumatoid arthritis data
vuong

Vuong's test for the comparison of non-nested copula mixed models for diagnostic test accuaracy studies
dvinesim

Simulation from a (truncated) quadrivariate D-vine copula
dcop

Bivariate copula densities
pcondcop

Bivariate copula conditional distribution functions
qcondcop

Bivariate copula conditional quantile functions
rmultinomVineCopulaREMADA

Simulation from multinomial quadrivariate (truncated) D-vine copula mixed models for diagnostic test accurracy studies accounting for non-evaluable outcomes
rcop

Simulation from parametric bivariate copula families
hybridCopulaREMADA

Maximum likelhood estimation for hybrid copula mixed models for combining case-control and cohort studies in meta-analysis of diagnostic tests
telomerase

The telomerase data
tau2par

Mapping of Kendall's tau and copula parameter