Prediction plot from jmrmlB()
plot.jmrmlB.RdPrediction plot from jmrmlB()
Usage
# S3 method for jmrmlB
plot(x, y, ...)Value
Returns prediction plot for the newdata using the model fitted through jmrmlB().
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
# \donttest{
##
library(JMbayes2)
library(joineRML)
jmrmlBModel<-jmrmlB(dtlong=new_long2[new_long2$id<=400,],
dtsurv=new_surv2[new_surv2$id<=400,],
longm=list(y~x7+visit,y~x7+visit),
survm=list(Surv(time,status)~x1+visit,
Surv(time_2,status_2)~x1+visit),
rd=list(~visit|id,~visit|id),
id='id',
timeVar='visit',
samplesize=200,
BIGdata=TRUE)
#> EM algorithm has converged!
#> Calculating post model fit statistics...
#> EM algorithm has converged!
#> Calculating post model fit statistics...
#> EM algorithm has converged!
#> Calculating post model fit statistics...
#> EM algorithm has converged!
#> Calculating post model fit statistics...
t0<-6
ndBIG<-new_long2[new_long2$id==10,]
ndBIG<-ndBIG[ndBIG$visit<t0,]
ndBIG$status<-0
ndBIG$time<-t0
ndBIG$time_2<-10
ndBIG$status_2<-0
plot(jmrmlBModel,ndBIG)
#>
#>
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##
# }