jmcsB: Joint model for Bidirectional survival data using 'FastJM'

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

Joint model for Bidirectional survival data using FastJM

Description

The function fits joint model for survival data with two events. It utilizes the FastJM package for obtaining the model parameter estimates.

Usage

jmcsB(
  dtlong,
  dtsurv,
  longm,
  survm,
  rd,
  id,
  timeVar,
  BIGdata = FALSE,
  samplesize = 200
)

Arguments

dtlong	longitudinal data
dtsurv	survival data with two event status along with event time
longm	longitudinal model e.g. list(serBilir~drug * year,serBilir ~ drug * year)
survm	survival model e.g. list(Surv(years,status2)~drug,Surv(time_2,status_2)~drug+age)
rd	random effect component e.g. list(~year|id,~year|id)
id	ID variable
timeVar	time variable
BIGdata	logical argument TRUE or FALSE
samplesize	samplesize for bigdata

Value

Estimated model parameters of Joint model with bidirectional survival data

Author(s)

Atanu Bhattacharjee, Bhrigu Kumar Rajbongshi and Gajendra Kumar Vishwakarma

References

Li, Shanpeng, et al. "Efficient Algorithms and Implementation of a Semiparametric Joint Model for Longitudinal and Competing Risk Data: With Applications to Massive Biobank Data." Computational and Mathematical Methods in Medicine 2022 (2022).

Bhattacharjee, A., Rajbongshi, B. K., & Vishwakarma, G. K. (2024). jmBIG: enhancing dynamic risk prediction and personalized medicine through joint modeling of longitudinal and survival data in big routinely collected data. BMC Medical Research Methodology, 24(1), 172.

Examples

library(FastJM)
library(JMbayes2)
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_jmcs<-jmcsB(dtlong=pbc2_new,dtsurv=new_pbc2id,
                  longm=list(serBilir~drug*year,
                             serBilir~drug*year),
                  survm=list(Surv(years,status2)~drug,
                             Surv(time_2,status_2)~drug+age),
                  rd=list(~1|id,~1|id),
                  id='id',timeVar='year')
model_jmcs

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