predJMbayes: Prediction using 'JMbayes2'

In jmBIG: Joint Longitudinal and Survival Model for Big Data

Prediction using JMbayes2

Description

prediction of survival probability and longitudinal marker using jmBayes2 for BIG data

Usage

predJMbayes(model, ids, process = "longitudinal", newdata, ...)

Arguments

model	fitted model object
ids	value of id
process	see jm
newdata	dataset having covariate information for the ids mentioned above.
...	other parameter options, see predict.jm

Value

list of predicted value for the given id

Examples

 
##
library(survival)
library(nlme)
library(dplyr)
jmcs1<-jmbayesBig(dtlong=long2,
dtsurv = surv2 ,
longm=y~ x7+visit,
survm=Surv(time,status)~x1+visit,
rd= ~ visit|id,
timeVar='visit',
nchain=1,
samplesize=200,
id='id')
mod3<-jmcs1
ydt<-long2%>%filter(id%in%c(900))
names(ydt)
cdt<-surv2[,'id']%>%filter(id%in%c(900))
names(cdt)
newdata<-full_join(ydt,cdt,by='id')
P2<-predJMbayes(model<-mod3,ids<-c(900),newdata=newdata,process = 'event')
plot(P2$p1[[1]])

##

   

jmBIG documentation built on May 29, 2024, 6:04 a.m.