plot.jmstB: Prediction plot from 'jmstB()'

In JMbdirect: Joint Model for Longitudinal and Multiple Time to Events Data

Prediction plot from jmstB()

Description

Prediction plot from jmstB()

Usage

## S3 method for class 'jmstB'
plot(x, y, ...)

Arguments

x	fitted model object
y	newdata
...	others

Value

Returns prediction plot for the newdata using the model fitted through jmstB().

Note

In the example code we use newdata as the data for ID 2 in the PBC2 dataset, it has follow up information till 8.832. Now suppose we want to look at the survival of ID 2 under joint model 1 after time 4 and for joint model 2 after time 9. For that we created the newdata as if the individual is followed till for a time period less than min(4,9).

Examples

 
##
library(JMbayes2)
library(rstanarm)
st_pbcid<-function(){
  new_pbcid<-pbc2.id
  new_pbcid$time_2<-rexp(n=nrow(pbc2.id),1/10)
  cen_time<-runif(nrow(pbc2.id),min(new_pbcid$time_2),max(new_pbcid$time_2))
  status_2<-ifelse(new_pbcid$time_2<cen_time,1,0)
  new_pbcid$status_2<-status_2
  new_pbcid$time_2<-ifelse(new_pbcid$time_2<cen_time,new_pbcid$time_2,cen_time)
  new_pbcid$time_2<-ifelse(new_pbcid$time_2<new_pbcid$years,new_pbcid$years,new_pbcid$time_2)
  new_pbcid
}
new_pbc2id<-st_pbcid()
pbc2$status_2<-rep(new_pbc2id$status_2,times=data.frame(table(pbc2$id))$Freq)
pbc2$time_2<-rep(new_pbc2id$time_2,times=data.frame(table(pbc2$id))$Freq)
pbc2_new<-pbc2[pbc2$id%in%c(1:50),]
new_pbc2id<-new_pbc2id[new_pbc2id$id%in%c(1:50),]
model_jmstBdirect<-jmstB(
  dtlong=pbc2_new,
  dtsurv = new_pbc2id,
  longm=list(serBilir ~ drug * year+(year|id),albumin~drug+year+(year|id)),
  survm=list(Surv(years,status2) ~ drug,Surv(time_2,status_2) ~ drug),
  timeVar="year",
  id='id',
  refresh=400,
  nchain=1)
t0<-4
nd<-pbc2[pbc2$id %in% c(2), ]
nd<-nd[nd$year<t0,]
nd$status2<-0
nd$years<-t0
nd$time_2<-9
nd$status_2<-0
plot(x=model_jmstBdirect,y = nd)
##

JMbdirect documentation built on April 12, 2025, 1:55 a.m.