survMCmulti: Survival analysis on multiple variables with MCMC

In SurviMChd: High Dimensional Survival Data Analysis with Markov Chain Monte Carlo

Survival analysis on multiple variables with MCMC

Description

Performs survival analysis using Cox Proportional Hazards with MCMC with an option to input select multiple variables.

Usage

survMCmulti(
  var1 = NULL,
  var2 = NULL,
  var3 = NULL,
  var4 = NULL,
  var5 = NULL,
  Time,
  Event,
  chains,
  adapt,
  iter,
  data
)

Arguments

var1	Variable name (first one)
var2	Variable name (second one)
var3	Variable name (third one)
var4	Variable name (fourth one)
var5	Variable name (fifth one)
Time	Variable/Column name containing the information on duration of survival
Event	Variable/Column name containing the information of survival event
chains	Number of chains to perform
adapt	Number of chains to perform
iter	Number of iterations to perform
data	High dimensional data having survival duration and event.

Details

The survival columns of the data should be arranged as follows - Death Death status=1 if died otherwise 0. OS Survival duration measured as 'OS'

Value

Data set containing Posterior HR estimates, SD, quantiles and meandeviance.

Author(s)

Atanu Bhattacharjee and Akash Pawar

References

Bhattacharjee, A. (2020). Bayesian Approaches in Oncology Using R and OpenBUGS. CRC Press.

See Also

survintMC

Examples

##
data(mcsurv)
survMCmulti(var1="x1",var2=NULL,var3="x3",var4="x2",
   var5="x4",Time="OS",Event="Death",chains=2,adapt=100,iter=1000,data=mcsurv)
##

SurviMChd documentation built on May 29, 2024, 6:20 a.m.