Simulation of two-stage recurrent events data based on Cox/Cox or Cox/Ghosh-Lin structure
Source:R/recreg.R
simGLcox.RdSimulation of two-stage recurrent events data based on Cox/Cox or Cox/Ghosh-Lin structure. type=3 will generate Cox/Cox twostage mode, type=2 will generate Ghosh-Lin/Cox model. If the variance is var.z=0, then generates data without any dependence or frailty. If model="twostage" then default is to generate data from Ghosh-Lin/Cox model, and if type=3 then will generate data with marginal Cox models (Cox/Cox). Simulation based on linear aproximation of hazard for two-stage models based on grid on time-scale. Must be sufficientyly fine.
Usage
simGLcox(
n,
base1,
drcumhaz,
var.z = 0,
r1 = NULL,
rd = NULL,
rc = NULL,
fz = NULL,
fdz = NULL,
model = c("twostage", "frailty", "shared"),
type = NULL,
share = 1,
cens = NULL,
nmin = 100,
nmax = 1000
)Arguments
- n
number of id's
- base1
baseline for cox/ghosh-lin models
- drcumhaz
baseline for terminal event
- var.z
variance of gamma frailty
- r1
relative risk term for baseline
- rd
relative risk term for terminal event
- rc
relative risk term for censorings
- fz
possible transformation (function) of frailty term
- fdz
possible transformation (function) of frailty term for death
- model
twostage, frailty, shared (partly shared two-stage model)
- type
type of simulation, default is decided based on model
to fit patly shared random effects model
- cens
censoring rate for exponential censoring
- nmin
default 100, at least nmin or number of rows of the two-baselines max(nmin,nrow(base1),nrow(drcumhaz)) points in time-grid from 0 to maximum time for base1
- nmax
default 1000, at most nmax points in time-grid