SDGM4: Survival Data Generation Method 4

In SurvMetrics: Predictive Evaluation Metrics in Survival Analysis

Survival Data Generation Method 4

Description

Survival data generation method. An example of the proportional hazards model where in the Cox model is expected to perform best.

Usage

SDGM4(N = 200, p = 15, c_step = 0.4)

Arguments

N	The sample size of the simulated dataset.
p	The covariate dimension of the simulated dataset.
c_step	The parameter which is used to control the censoring rate.

Value

the simulated dataset

Author(s)

Hanpu Zhou [e-mail]

References

Steingrimsson, J. A. , Diao, L. , & Strawderman, R. L. . (2019). Censoring unbiased regression trees and ensembles. Journal of the American Statistical Association, 114.

Zhu, R. , & Kosorok, M. R. . (2012). Recursively imputed survival trees. Journal of the American Statistical Association, 107(497), 331-340.

Ishwaran, H., Kogalur, U. B., Gorodeski, E.Z., Minn, A.J., & Lauer, M. S. . (2010). High-dimensional variable selection for survival data. Journal of the American Statistical Association, 105(489), 205-217.

Examples

SDGM4(N = 200, p = 15, c_step = 0.4)

SurvMetrics documentation built on Sept. 4, 2022, 1:06 a.m.