rsurv: rsurv
In DouglasMesquita/RASCO: An R Package to Alleviate Spatial Confounding

rsurv

R Documentation

rsurv

Description

Generating data with spatial confounding

Usage

rsurv(
  n_id,
  coefs = c(0.1, 0.4, -0.3),
  cens = 0,
  cens_type = "interval",
  hazard = "weibull",
  hazard_params = hazard_dft(),
  spatial = "ICAR",
  neigh = NULL,
  W = NULL,
  tau = 1,
  confounding = "none",
  proj = "none",
  sd_x = 0,
  X = NULL,
  scale = TRUE
)

Arguments

`n_id`	vector with the number of individuals in each region to be generated.
`coefs`	vector of coefficients.
`cens`	proportion of censoring.
`cens_type`	censoring scheme: "none", "left", "right" or "interval".
`hazard`	hazard model: "exponential", "weibull" or "pwe" for piecewise exponential.
`hazard_params`	named list with parameters for the hazard model: hazard_dft().
`spatial`	spatial model: "none" for the conventional Cox model, "gamma" for an independent gamma frailty, "lognormal" for an independent lognormal frailty, "ICAR" or "BYM" for spatial structured models.
`neigh`	neighborhood structure. A `SpatialPolygonsDataFrame` object.
`W`	adjacency matrix.
`tau`	precision for ICAR and BYM models.
`confounding`	"none", "linear", "quadratic" or "cubic".
`proj`	"none", "rhz", "hh" or "spock".
`sd_x`	standard deviation to generating confounding.
`X`	matrix of covariates. Default = NULL.
`scale`	scale X. TRUE or FALSE.