rmultinomVineCopulaREMADA | R Documentation |
Simulation from multinomial quadrivariate (truncated) D-vine copula mixed models for diagnostic test accurracy studies accounting for non-evaluable outcomes
rmultinomVineCopulaREMADA.norm(N,p,si,taus,qcond1, pcond1,tau2par1,qcond2, pcond2,tau2par2) rmultinomVineCopulaREMADA.beta(N,p,g,taus,qcond1, pcond1,tau2par1,qcond2, pcond2,tau2par2)
N |
sample size |
p |
Vector (π_1,π_2,π_3) of sensitivity/specificity/prevalence |
si |
Vector (σ_1,σ_2,σ_3) of variability; normal margins |
g |
Vector (γ_1,γ_2,γ_3) of variability; beta margins |
taus |
Kendall's tau values |
qcond1 |
function for the inverse conditional copula cdf at the (1,2) and (3,4) bivariate margin |
pcond1 |
function for the conditional copula cdf at the (1,2) and (3,4) bivariate margin |
tau2par1 |
function for maping Kendall's tau at the (1,2) and (3,4) bivariate margin to copula parameter |
qcond2 |
function for the inverse conditional copula cdf at the (2,3) bivariate margin |
pcond2 |
function for the conditional copula cdf at the (2,3) bivariate margin |
tau2par2 |
function for maping Kendall's tau at the (2,3) bivariate margin to copula parameter |
Simulated data with 6 columns and N rows.
the number of true positives
the number of false negatives
the number of false positives
the number of true negatives
the number of non-evaluable positives
the number of non-evaluable negatives
Nikoloulopoulos, A.K. (2020) A multinomial quadrivariate D-vine copula mixed model for diagnostic studies meta-analysis in the presence of non-evaluable subjects. Statistical Methods in Medical Research, 29 (10), 2988–3005. doi: 10.1177/0962280220913898.
dvinesim
N=30 p=c(0.898745016,0.766105342,0.059168715,0.109217888) g=c(0.090270947,0.079469009,0.367463579,0.154976269) taus=c( 0.82050793,-0.51867629,0.26457961) qcond1=qcondcln180 pcond1=pcondcln180 tau2par1=tau2par.cln180 qcond2=qcondcln90 pcond2=pcondcln90 tau2par2=tau2par.cln90 out=rmultinomVineCopulaREMADA.beta(N,p,g,taus,qcond1,pcond1,tau2par1,qcond2,pcond2,tau2par2) TP=out[,1] NEP=out[,2] FN=out[,3] TN=out[,4] NEN=out[,5] FP=out[,6]
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