intcensROC {intcensROC} | R Documentation |
Compute the ROC curves for Interval Censored Survival Data
Description
A method to compute the receiver operating characteristic (ROC) curve for the interval censored survival data based on a spline function based constrained maximum likelihood estimator. The maximization process of likelihood is carried out by generalized gradient projection method.
Usage
intcensROC(U, V, Marker, Delta, PredictTime, gridNumber = 500)
Arguments
U |
An array contains left end time points of the observation time range for the interval censored data. |
V |
An array contains right end time points of the observation time range for the interval censored data. |
Marker |
An array contains marker levels for the samples. |
Delta |
An array of indicator for the censored type, use 1, 2, 3 for event happened before the left bound time, within the defined time range, and after. |
PredictTime |
A scalar indicates the predict time. |
gridNumber |
A integer for the number of gird for the ROC curve, the default value is 500. |
Value
A dataframe
with two columes
tp |
A array for true positive rate for different marker levels in the range of 0 to 1. |
fp |
A array for false positive rate for different marker levels in the range of 0 to 1. |
References
Wu, Yuan; Zhang, Ying. Partially monotone tensor spline estimation of the joint distribution function with bivariate current status data. Ann. Statist. 40, 2012, 1609-1636 <doi:10.1214/12-AOS1016>
Examples
## example data
U <- runif(100, min = 0.1, max = 5)
V <- runif(100, min = 0.1, max = 5) + U
Marker <- runif(100, min = 5, max = 10)
Delta <- sample.int(3, size = 100, replace = TRUE)
pTime <- 4
## compute the ROC curve
res <- intcensROC(U, V, Marker, Delta, pTime, gridNumber = 500)
head(res)