print.jmbayesBig

print method for class 'jmbayesBig'

Usage

# S3 method for jmbayesBig
print(x, ...)

Arguments

x

fitted object

...

others

Value

prints table containing various parameter estimates, SE, P- value for both survival and longitudinal submodel, if the model is bayesian it includes their credible interval too.

Examples

 # \donttest{
##
library(survival)
library(dplyr)

#################################
mod3<-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')
print(mod3)
#> 
#>  Joint model for Big data using jmbayes2
#>  Call: 
#> jmbayesBig(dtlong = long2, dtsurv = surv2, longm = y ~ x7 + visit, 
#>     survm = Surv(time, status) ~ x1 + visit, samplesize = 200, 
#>     rd = ~visit | id, timeVar = "visit", nchain = 1, id = "id")
#> 
#> 
#>  Total observation in longitudinal data: 1000 
#> 
#>  Chunk size: 200 
#> 
#>  Longitudinal process: 
#>               Mean StDev   2.5%  97.5% Pvalue
#> (Intercept)  8.848 0.455  7.319  9.123  0.000
#> x7          -0.023 0.007 -0.028 -0.001  0.001
#> visit       -0.093 0.038 -0.149 -0.002  0.014
#> sigma        0.778 0.020  0.740  0.821  0.000
#> 
#>  Survival process: 
#>          Mean StDev   2.5% 97.5% Pvalue
#> x11   -0.054 0.312 -0.748 0.451  0.863
#> visit -0.102 0.064 -0.101 0.158  0.111
#> Mean  -0.148 0.057 -0.229 0.016  0.010
#> 
#>  Random effects covariance matrix:
#>    D[1, 1]    D[2, 1]    D[2, 2] 
#>  1.9874728 -0.3173188  0.1265917 
   # }