# IDI and NRI for comparing competing risk prediction models with censored survival data

### Description

Performs inference for a class of measures to compare competing risk prediction models with censored survival data. The class includes the integrated discrimination improvement index (IDI) and category-less net reclassification index (NRI).

### Details

Package: | survIDINRI |

Type: | Package |

Version: | 1.1-1 |

Date: | 2013-4-8 |

License: | GPL-2 |

### Author(s)

Hajime Uno, Tianxi Cai

Maintainer: Hajime Uno <huno@jimmy.harvard.edu>

### References

Pencina MJ, D'Agostino RB, Steyerberg EW. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Statistics in Medicine 2011. doi:10.1002/sim.5647

Uno H, Tian L, Cai T, Kohane IS, Wei LJ. A unified inference procedure for a class of measures to assess improvement in risk prediction systems with survival data, Statistics in Medicine 2012. doi:10.1002/sim.5647

### See Also

survC1-package

### Examples

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
#--- sample data (pbc in survival package) ---
D=subset(pbc, select=c("time","status","age","albumin","edema","protime","bili"))
D$status=as.numeric(D$status==2)
D=D[!is.na(apply(D,1,mean)),] ; dim(D)
mydata=D[1:100,]
t0=365*5
indata1=mydata;
indata0=mydata[,-7] ; n=nrow(D) ;
covs1<-as.matrix(indata1[,c(-1,-2)])
covs0<-as.matrix(indata0[,c(-1,-2)])
#--- inference ---
x<-IDI.INF(mydata[,1:2], covs0, covs1, t0, npert=200) ;
#--- results ---
IDI.INF.OUT(x) ;
#--- Graphical presentaion of the estimates ---
# IDI.INF.GRAPH(x) ;
``` |

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