simData4cure function

Simulate Data from Cox Cure Model with Uncertain Event Status

simData4cure(
  nSubject = 1000,
  shape = 2,
  scale = 0.1,
  lambda_censor = 1,
  max_censor = Inf,
  p1 = 0.9,
  p2 = 0.9,
  p3 = 0.9,
  survMat,
  cureMat = survMat,
  b0 = stats::binomial()$linkfun(0.7),
  survCoef = rep(1, ncol(survMat)),
  cureCoef = rep(1, ncol(cureMat)),
  ...
)

Arguments

• nSubject: A positive integer specifying number of subjects.
• shape: A positive number specifying the shape parameter of the distribution of the event times.
• scale: A positive number specifying the scale parameter of the distribution of the event times.
• lambda_censor: A positive number specifying the rate parameter of the exponential distribution for generating censoring times.
• max_censor: A positive number specifying the largest censoring time.
• p1: A number between 0 and 1 specifying the probability of simulating events with observed event indicators given the simulated event times.
• p2: A number between 0 and 1 specifying the probability of simulating susceptible censoring times with observed event status given the simulated susceptible censoring times.
• p3: A number between 0 and 1 specifying the probability of simulating cured censoring times with observed event status given the simulated cured censoring times.
• survMat: A numeric matrix representing the design matrix of the survival model part.
• cureMat: A numeric matrix representing the design matrix excluding intercept of the cure rate model part.
• b0: A number representing the intercept term for the cure rate model part.
• survCoef: A numeric vector for the covariate coefficients of the survival model part.
• cureCoef: A numeric vector for the covariate coefficients of the cure model part.
• ...: Other arguments not used currently.

Returns

A data.frame with the following columns:

• obs_time: Observed event/survival times.
• obs_event: Observed event status.
• event_time: Underlying true event times.
• censor_time: underlying true censoring times.
• oracle_event: underlying true event indicators.
• oracle_cure: underlying true cure indicators.
• case: underlying true case labels.

Examples

## see examples of function cox_cure

References

Wang, W., Luo, C., Aseltine, R. H., Wang, F., Yan, J., & Chen, K. (2020). Suicide Risk Modeling with Uncertain Diagnostic Records. arXiv preprint arXiv:2009.02597.