Simulate a Node Using Cox-Regression

Data from the parents is used to generate the node using cox-regression using the method of Bender et al. (2005).

Usage

node_cox(data, parents, formula=NULL, betas, surv_dist, lambda, gamma,
         cens_dist, cens_args, name)

Arguments

data: A data.table (or something that can be coerced to a data.table) containing all columns specified by parents.
parents: A character vector specifying the names of the parents that this particular child node has. If non-linear combinations or interaction effects should be included, the user may specify the formula argument instead.
formula: An optional formula object to describe how the node should be generated or NULL (default). If supplied it should start with ~, having nothing else on the left hand side. The right hand side may contain any valid formula syntax, such as A + B or A + B + I(A^2), allowing non-linear effects. If this argument is defined, there is no need to define the parents argument. For example, using parents=c("A", "B") is equal to using formula= ~ A + B.
betas: A numeric vector with length equal to parents, specifying the causal beta coefficients used to generate the node.
surv_dist: A single character specifying the distribution that should be used when generating the survival times. Can be either "weibull" or "exponential".
lambda: A single number used as parameter defined by surv_dist.
gamma: A single number used as parameter defined by surv_dist.
cens_dist: A single character naming the distribution function that should be used to generate the censoring times. For example, "runif" could be used to generate uniformly distributed censoring times. Set to NULL to get no censoring.
cens_args: A list of named arguments which will be passed to the function specified by the cens_dist argument.
name: A single character string specifying the name of the node.

Details

The survival times are generated according to the cox proportional-hazards regression model as defined by the user. How exactly the data-generation works is described in detail in Bender et al. (2005). To also include censoring, this function allows the user to supply a function that generates random censoring times. If the censoring time is smaller than the generated survival time, the individual is considered censored.

Unlike the other node type functions, this function adds two columns to the resulting dataset instead of one. The first column is called paste0(name, "_event") and is a logical variable, where TRUE indicates that the event has happened and FALSE indicates right-censoring. The second column is named paste0(name, "_time") and includes the survival or censoring time corresponding to the previously mentioned event indicator. This is the standard format for right-censored time-to-event data without time-varying covariates.

To simulate more complex time-to-event data, the user may need to use the sim_discrete_time function instead.

References

Bender R, Augustin T, Blettner M. Generating survival times to simulate Cox proportional hazards models. Statistics in Medicine. 2005; 24 (11): 1713-1723.

Author

Robin Denz

Value

Returns a data.table of length nrow(data) containing two columns. Both starting with the nodes name and ending with _event and _time. The first is a logical vector, the second a numeric one.

Examples

library(simDAG)

set.seed(3454)

# define DAG
dag <- empty_dag() +
  node("age", type="rnorm", mean=50, sd=4) +
  node("sex", type="rbernoulli", p=0.5) +
  node("death", type="cox", parents=c("sex", "age"), betas=c(1.1, 0.4),
       surv_dist="weibull", lambda=1.1, gamma=0.7, cens_dist="runif",
       cens_args=list(min=0, max=1))

sim_dat <- sim_from_dag(dag=dag, n_sim=1000)