| rocNIT {rocNIT} | R Documentation |
Non-Inferiority Test for Paired ROC Curves
Description
Non-inferiority test and diagnostic test are very important in clinical trails. This package is to get a p value of the non-inferiority test for ROC curves from diagnostic test using the bootstrap method.
Usage
rocNIT(BNO,DATA,cVAL1,cVAL2,cGOLD,DELTA,ALPHA,seed)
Arguments
BNO |
the times of the sampling of bootstrap |
DATA |
the dataset including 3 variables at least: VAL1,VAL2,GOLD |
cVAL1 |
the column number of the first numeric variable |
cVAL2 |
the column number of the second numeric variable |
cGOLD |
the column number of the golden variable which should be binary |
DELTA |
the non-inferiority margin, default is 0.05 |
ALPHA |
the significant level, default is 0.05 |
seed |
the seed for the sampling of bootstrap, default is 2016 |
Value
AREA1 |
the AUC for the first variable |
AREASE1 |
the SE of the AUC for the first variable |
AREA2 |
the AUC for the second variable |
AREASE2 |
the SE of the AUC for the second variable |
bCIL |
the lower limit of CI from bootstrap sampling |
bCIU |
the upper limit of CI from bootstrap sampling |
Z |
the statistic to get the p value |
P |
the p value of the non-inferiority test, P < ALPHA means a significant non-inferiority |
Note
Referenced from Jen-Pei Liu et al. Tests of equivalence and non-inferiority for diagnostic accuracy based on the paired areas under ROC curves. STATISTICS IN MEDICINE. DOI: 10.1002/sim.2358
Author(s)
Zhicheng Du<dgdzc@hotmail.com>, Yuantao Hao<haoyt@mail.sysu.edu.cn>
See Also
nothing
Examples
VAL1=c(rnorm(50,mean=0),rnorm(50,mean=0)+0.5)
VAL2=c(rnorm(50,mean=0),rnorm(50,mean=0)+1)
GOLD=rep(1:2,each=50)
data=data.frame(GOLD,VAL1,VAL2)
rocNIT(BNO=200,DATA=data,cVAL1=2,cVAL2=3,cGOLD=1,DELTA=0.05,ALPHA=0.05,seed=2016)