jmstanBig: Joint model for BIG data using rstanarm

In jmBIG: Joint Longitudinal and Survival Model for Big Data

Joint model for BIG data using rstanarm

Description

function for joint model in BIG DATA using rstanarm package

Usage

jmstanBig(
  dtlong,
  dtsurv,
  longm,
  survm,
  samplesize = 50,
  time_var,
  id,
  nchain = 1,
  refresh = 2000
)

Arguments

dtlong	longitudinal dataset, which contains id,visit time,longitudinal measurements along with various covariates
dtsurv	survival dataset corresponding to the longitudinal dataset, with survival status and survival time
longm	model for longitudinal response
survm	survival model
samplesize	sample size to divide the Big data
time_var	time variable in longitudinal model, included in the longitudinal data
id	name of id column in longitudinal dataset
nchain	number of chain for MCMC
refresh	refresh rate for MCMC chain

Value

returns a list containing various output which are useful for prediction.

Author(s)

Atanu Bhattacharjee, Bhrigu Kumar Rajbongshi and Gajendra Kumar Vishwakarma

References

Goodrich, B., et al. "rstanarm: Bayesian applied regression modeling via Stan. R package version 2.17. 4." Online< http://mc-stan. org (2018).

See Also

jmbayesBig,jmcsBig,joinRMLBig

Examples

 
##
library(survival)
library(dplyr)
fit3<-jmstanBig(dtlong=long2,dtsurv = surv2,longm=y~ x7+visit+(1|id),
survm=Surv(time,status)~x1+visit,samplesize=200,time_var='visit',id='id')
P2<-postTraj(model<-fit3,m<-1,ids<-c(1,2,100))
pp1<-plot(P2$p1[[1]],plot_observed = TRUE)
pp2<-plot(P2$p1[[2]],plot_observed = TRUE)
pp3<-plot(P2$p1[[3]],plot_observed = TRUE)
##

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