survfitJMCS: Prediction using 'FastJM'

In jmBIG: Joint Longitudinal and Survival Model for Big Data

Prediction using FastJM

Description

prediction of survival probability using FastJM for BIG data

Usage

survfitJMCS(model, ids, u, method = "GH", obs.time)

Arguments

model	fitted model object
ids	value of id
u	see survfitjmcs
method	options are 'Laplace','GH'
obs.time	vector which represents time variable in the longitudinal data

Value

list of predicted value for the given id along with other information relevant for survival probability confidence plot

Examples

  
##
library(survival)
library(dplyr)
jmcs1<-jmcsBig(dtlong=data.frame(long2),
dtsurv = data.frame(surv2),
longm=y~ x7+visit,
survm=Surv(time,status)~x1+visit,
rd= ~ visit|id,
samplesize=200,id='id')
mod2<-jmcs1
P2<-survfitJMCS(model<-mod2,ids<-c(5),u<-seq(surv2[surv2$id==5,]$time,
surv2[surv2$id==5,]$time+10,0.2),obs.time='time')
print(P2)
##
  

jmBIG documentation built on April 3, 2025, 9:57 p.m.