survivAURC: A function that calculates the area under a curve constructed...

In RCASPAR: A package for survival time prediction based on a piecewise baseline hazard Cox regression model.

Description

This function plots the individual area under the ROC curves of different time points against the time at which they were evaluated, and calculates the area under that curve.

Usage

survivAURC(Stime, status, marker, entry = NULL, cut.values = NULL, time.max = 20, by = 1)

Arguments

Stime	The observed survival times of the patients.
status	The censoring status of the patient. 1 for a censored patient, and 0 for a patient who has an event.
marker	The predicted survival time of the patients.
entry	The time of entry of the patients, set to NULL by default.
cut.values	The cut off values for which the ROC curves are to be constructed.
time.max	The maximum time point for which the area under a ROC curve is to be plotted.
by	The step size between every ROC curve estimated and the next.

Details

The calculations for the Area under the ROC curves at each time point is done according to Patrick Heagerty's survivalROC function in the survivalROC package in R. It is a value indicating the performance of the predictor when used on the results of both functions STpredictor.BLH and STpredictor.xv.BLH.

Value

AUC	The value of the area under the curve generated
AUeachROC	A vector with the values of the area under the individual ROC curves

A plot of the Area under the ROC curves against their corresponding time points.

Author(s)

Douaa Mugahid

References

Heagerty,P., Lumely T. & Pepe M.(2000). Time-dependent ROC curves for censored survival data & a diagnostic marker. Biometrics, 56(2), 337-344.

See Also

survivROC

Examples

True_STs <- c(1.416667,2.75,2.416667,2.583333,2.166667,2.5,2.5,1.833333,1.25,0.6666667,1,6.583333,6.5,6.666667,2.75,1.666667,1.166667,2.833333,3.583333,6.166667,6.166667,
3.416667,6.083333,1.833333,5.583333,0.75,5.75,5.5,0.5833333,7.666667,5,2.833333,1.333333,5.083333,0.8333333,1.5,4.75,3.416667,4.666667,1.916667,4.666667,7.416667,0.9166667,
1.083333,3.75,3.25,3,2.416667,2.75,2.5,2.666667,4.5,4.416667,1.5,0.8333333,3.166667,3.833333,3.833333,0.4166667,3.333333,2.75,3.083333,0.3333333,0.25,0.6666667,1.833333,
2.333333,3.416667,3.416667,3,0.6666667,0.75,2.166667,1,1.416667,1.333333,1.166667,1.166667,0.4166667,1.25,1.166667,1.083333)
Predicted_STs <- c(6.030591,6.014457,3.545584,5.414229,6.41576,9.393992,5.542331,6.890859,8.090213,4.98545,2.77357,6.275699,9.163978,7.511511,9.531218,7.63715,10.08977,
11.12364,3.982502,5.441881,12.61404,12.21851,17.05850,12.78141,16.22795,21.48544,6.281354,13.83925,8.859929,6.104142,8.255909,2.335526,6.564962,2.335761,9.33772,12.62540,
10.97276,15.63089,8.01967,5.817267,5.59897,4.340784,32.40319,33.74123,27.45024,26.31024,26.88833,24.34707,32.06541,38.90473,17.37102,15.11059,8.772035,14.24816,7.852889,
7.79996,5.601459,2.802408,35.77047,24.34717,30.65796,25.93927,20.64544,22.04807,19.15037,23.83430,1.876557,3.937208,6.526354,5.886377,9.301074,12.4657,14.49783,15.41502,
2.860931,2.541947,4.543111,4.525553,4.148272,3.986912,6.246755,6.89523)
censored <- c(0,1,1,1,1,0,1,1,0,1,0,1,1,1,1,0,0,0,0,1,1,1,1,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,0,1,1,0,0,1,1,1,0,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,0,0,0,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,
1)
survivAURC(Stime=True_STs,status=censored, marker=Predicted_STs,time.max=5)

Example output

$AUC
[1] 2.16072

$AUeachROC
[1] 1.0000000 0.3000696 0.3558260 0.3893873 0.4102913 0.4102913

RCASPAR documentation built on Nov. 8, 2020, 6:56 p.m.