Description Usage Arguments Details Value Author(s) References See Also Examples
Compute area under the ROC curve for several values of time horizon
1 |
X |
n by S matrix of longitudinal score/biomarker for i-th subject at j-th occasion (NA if unmeasured) |
etime |
n vector with follow-up times |
status |
n vector with event indicators |
u |
Lower limit for evaluation of sensitivity and
specificity. Defaults to |
tt |
A vector of upper limits (time-horizons) for evaluation of sensitivity and specificity. |
s |
Scalar number of measurements/visits to use for each subject. s<=S |
vtimes |
S vector with visit times |
fc |
Events are defined as fc = 1. Defaults to $I(cup X(t_j)>cutoff)$ |
plot |
Do we plot the AUCs? Defaults to |
Area under the ROC curve is computed for each value of the vector
tt. The resulting vector is returned. If plot=TRUE
(which is
the default) also a plot of tt vs AUC is displayed.
A vector with AUCs
Alessio Farcomeni alessio.farcomeni@uniroma1.it
Barbati, G. and Farcomeni, A. (2017) Prognostic assessment of repeatedly measured time-dependent biomarkers, with application to dilated cardiomuopathy, Statistical Methods & Applications, in press
roc, butstrap, auc
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | # parameters
n=25
tt=3
Tmax=10
u=1.5
s=2
vtimes=c(0,1,2,5)
# generate data
ngrid=1000
ts=seq(0,Tmax,length=ngrid)
X2=matrix(rnorm(n*ngrid,0,0.1),n,ngrid)
for(i in 1:n) {
sa=sample(ngrid/6,1)
vals=sample(3,1)-1
X2[i,1:sa[1]]=vals[1]+X2[i,1:sa[1]]
X2[i,(sa[1]+1):ngrid]=vals[1]+sample(c(-2,2),1)+X2[i,(sa[1]+1):ngrid]
}
S1=matrix(sample(4,n,replace=TRUE),n,length(vtimes))
S2=matrix(NA,n,length(vtimes))
S2[,1]=X2[,1]
for(j in 2:length(vtimes)) {
tm=which.min(abs(ts-vtimes[j]))
S2[,j]=X2[,tm]}
cens=runif(n)
ripart=1-exp(-0.01*apply(exp(X2),1,cumsum)*ts/1:ngrid)
Ti=rep(NA,n)
for(i in 1:n) {
Ti[i]=ts[which.min(abs(ripart[,i]-cens[i]))]
}
cens=runif(n,0,Tmax*2)
delta=ifelse(cens>Ti,1,0)
Ti[cens<Ti]=cens[cens<Ti]
##
## an important marker
aucs=plotAUC(S2,Ti,delta,u,seq(2,5,length=5),s,vtimes)
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