jmrmlB {JMbdirect} | R Documentation |
Joint model for Bidirectional survival data using joineRML
Description
The function fits joint model for survival data with two events. It utilizes the joineRML package for obtaining the model parameter estimates.
Usage
jmrmlB(
dtlong,
dtsurv,
longm,
survm,
rd,
timeVar,
id,
samplesize = 200,
BIGdata = FALSE
)
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) |
timeVar |
time variable |
id |
ID variable |
samplesize |
samplesize for bigdata |
BIGdata |
logical argument TRUE or FALSE |
Value
Estimated model parameters of Joint model with bidirectional survival data
Author(s)
Atanu Bhattacharjee, Bhrigu Kumar Rajbongshi and Gajendra Kumar Vishwakarma
References
Hickey, Graeme L., et al. "joineRML: a joint model and software package for time-to-event and multivariate longitudinal outcomes." BMC medical research methodology 18 (2018): 1-14.
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(JMbayes2)
library(joineRML)
jmrmlBModel<-jmrmlB(dtlong=new_long2[new_long2$id%in%c(1:80),],
dtsurv=new_surv2[new_surv2$id%in%c(1:80),],
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=40,BIGdata=TRUE)
jmrmlBModel
##