flassomsm (version 0.1.0)

simdata: simdata

Description

Simulation of a multi-state model with \(n\) no. of states.

Usage

simdata(
  seed = 123,
  n = 1000,
  dist = "weibull",
  cdist = "exponential",
  cparams = list(rate = 0.1),
  lambdas,
  gammas,
  beta_list,
  cov_means,
  cov_sds,
  trans_list,
  state_names
)

Value

a multi-state dataframe with given number of states, corresponding status and the covariate vector

Arguments

seed

Random seed for reproducibility

n

Number of subjects

dist

distribution to follow for baseline hazard ("exponential", "weibull", "gompertz")

cdist

distribution to follow for censoring distribution ("uniform", "exponential", "weibull")

cparams

parameter vector for censoring distribution

lambdas

scale parameter of the baseline distribution

gammas

shape parameter of the baseline distribution

beta_list

a list containing coefficients for the covariates to be generated, each value corresponds to one transition

cov_means

mean value of each of the covariates

cov_sds

standard deviation of each of the covariates

trans_list

transition matrix of the multi-state model based on number of states

state_names

states of the multi-state model

Author

Atanu Bhattacharjee,Gajendra Kumar Vishwakarma,Abhipsa Tripathy

Details

This function is used for simulating a multi-state model with \(n\) no. of states and status corresponding to each state along with a number of covariates both continuous or categorical.

Examples

##
msdata_4state <- simdata(seed=123,n=1000,dist="weibull",cdist="exponential",
                 cparams=list(rate = 0.1),lambdas=c(0.1, 0.2, 0.3, 0.4),
                 gammas=c(1.5, 2, 2.5, 2.6),beta_list=list(c(-0.05, 0.01, 0.5, 0.6),
                 c(-0.03, 0.02, 0.07, 0.08),c(-0.04, 0.03, 0.04, -0.03),
                 c(-0.05, 0.05, 0.6, 0.8)),cov_means=c(0, 10, 2, 3),cov_sds=c(1,20,5,1.05),
                 trans_list=list(c(2, 3, 4, 5),c(3, 4, 5),c(4, 5), c(5), c()),
                 state_names=c("Tx", "Rec", "Death", "Reldeath", "srv"))
##