ggplot_roc {dscoreMSM} | R Documentation |
Reciever Operating Curve
Description
this function provides roc plot for coxph model fitted before and after survival proximity score matching.
Usage
ggplot_roc(
trns,
model1,
model2,
data1,
data2,
folder_path = NULL,
times = NULL
)
Arguments
trns |
transition number for the multistate model |
model1 |
fitted object from coxPH (before SPSM) |
model2 |
fitted object from coxPH (after SPSM) |
data1 |
dataset used for model1 |
data2 |
dataset used for model2 |
folder_path |
default is NULL. if folder_path is provided then plots will be saved there automitically. |
times |
default is NULL. time at which TP and FP values are calculated. |
Value
returns roc plot for model1 and model2
Author(s)
Atanu Bhattacharjee, Bhrigu Kumar Rajbongshi and Gajendra Kumar Vishwakarma
References
Vishwakarma, G. K., Bhattacherjee, A., Rajbongshi, B. K., & Tripathy, A. (2024). Censored imputation of time to event outcome through survival proximity score method. Journal of Computational and Applied Mathematics, 116103;
Bhattacharjee, A., Vishwakarma, G. K., Tripathy, A., & Rajbongshi, B. K. (2024). Competing risk multistate censored data modeling by propensity score matching method. Scientific Reports, 14(1), 4368.
See Also
Examples
##
library(mstate)
data(EBMTdata)
data(EBMTupdate)
tmat<-transMat(x=list(c(2,3),c(3),c()),
names=c("Tx","Rec","Death"))
covs<-c("dissub","age","drmatch","tcd","prtime","x1","x2","x3","x4")
msbmt<-msprep(time=c(NA,"prtime","rfstime"),
status=c(NA,"prstat","rfsstat"),
data=EBMTdata,trans=tmat,keep=covs)
msbmt1<-msprep(time=c(NA,"prtime","rfstime"),
status=c(NA,"prstat","rfsstat"),
data=EBMTupdate,trans=tmat,keep=covs)
msph3<-coxph(Surv(time,status)~dissub+age+drmatch+tcd+
frailty(id,distribution='gamma'),data=msbmt[msbmt$trans==3,])
msph33<-coxph(Surv(Tstart,Tstop,status)~dissub+age +drmatch+ tcd+
frailty(id,distribution='gamma'),data=msbmt1[msbmt1$trans==3,])
ggplot_roc(trns=3,model1=msph3,model2=msph33,
data1=msbmt,data2=msbmt1)
##