Compute sensitivity and specificity
sensspec.s(X,etime,status,u=NULL,tt,s,vtimes,cutoff=0,fc=NULL)n by S matrix of longitudinal score/biomarker for i-th subject at j-th occasion (NA if unmeasured)
n vector with follow-up times
n vector with event indicators
Lower limit for evaluation of sensitivity and
specificity. Defaults to max(vtimes[s]) (see below)
Upper limit (time-horizon) for evaluation of sensitivity and specificity.
n vector of measurements/visits to use for each subject. all(s<=S)
S vector with visit times
cutoff for definining events. Defaults to 0
Events are defined as fc = 1. Defaults to $I(cup X(t_j)>cutoff)$
A vector with the following elements:
sens |
Sensitivity at the cutoff |
spec |
Specificity at the cutoff |
Sensitivity and specificities for a time-dependent multiply-measured marker are defined as
Se(t,c,s,u) = Pr(f_c(X(t_1),X(t_2),...,X(t_s_i))| u <= T <= t),
and
Sp(t,c,s,u) = 1-Pr(f_c(X(t_1),X(t_2),...,X(t_s_i)) | T > t)
for some fixed f_c, where c is a cutoff. The default for f_c is that a positive diagnosis is given as soon as any measurement among the s considered is above the threshold.
Barbati, G. and Farcomeni, A. (2017) Prognostic assessment of repeatedly measured time-dependent biomarkers, with application to dilated cardiomuopathy, Statistical Methods \& Applications, in press