MK2016

Data on 30 studies from a systematic review for diagnostic accuracy studies of coronary computed tomography angiography for the detection of coronary artery disease.

datasets

The bivariate copula mixed model for meta-analysis of diagnostic test accuracy studies in Nikoloulopoulos (2015) <doi:10.1002/sim.6595> and Nikoloulopoulos (2018) <doi:10.1007/s10182-017-0299-y>. The vine copula mixed model for meta-analysis of diagnostic test accuracy studies accounting for disease prevalence in Nikoloulopoulos (2017) <doi:10.1177/0962280215596769> and also accounting for non-evaluable subjects in Nikoloulopoulos (2020) <doi:10.1515/ijb-2019-0107>. The hybrid vine copula mixed model for meta-analysis of diagnostic test accuracy case-control and cohort studies in Nikoloulopoulos (2018) <doi:10.1177/0962280216682376>. The D-vine copula mixed model for meta-analysis and comparison of two diagnostic tests in Nikoloulopoulos (2019) <doi:10.1177/0962280218796685>. The multinomial quadrivariate D-vine copula mixed model for meta-analysis of diagnostic tests with non-evaluable subjects in Nikoloulopoulos (2020) <doi:10.1177/0962280220913898>. The one-factor copula mixed model for joint meta-analysis of multiple diagnostic tests in Nikoloulopoulos (2022) <doi:10.1111/rssa.12838>. The multinomial six-variate 1-truncated D-vine copula mixed model for meta-analysis of two diagnostic tests accounting for within and between studies dependence in Nikoloulopoulos (2024) <doi:10.1177/09622802241269645>. The 1-truncated D-vine copula mixed models for meta-analysis of diagnostic accuracy studies without a gold standard (Nikoloulopoulos, 2024).

Aristidis Nikoloulopoulos

CopulaREMADA

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

MK2016 function

A data frame with 30 observations on the following 6 variables.<dl>
 <dt>TP</dt>
<dd>the number of true positives</dd><dt>FN</dt>
<dd>the number of false negatives</dd><dt>FP</dt>
<dd>the number of false positives</dd><dt>TN</dt>
<dd>the number of true negatives</dd><dt>NEP</dt>
<dd>the number of non-evaluable positives</dd><dt>NEN</dt>
<dd>the number of non-evaluable negatives</dd>
</dl>

Format

The coronary CT angiography data in Menke and Kowalski (2016). — MK2016

A data frame with 30 observations on the following 6 variables.<dl>
 <dt>TP</dt>
<dd>the number of true positives</dd>

<dt>FN</dt>
<dd>the number of false negatives</dd>

<dt>FP</dt>
<dd>the number of false positives</dd>

<dt>TN</dt>
<dd>the number of true negatives</dd>

<dt>NEP</dt>
<dd>the number of non-evaluable positives</dd>

<dt>NEN</dt>
<dd>the number of non-evaluable negatives</dd>


</dl>

MK2016: The coronary CT angiography data in Menke and Kowalski (2016).

Description

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References