SIM.FUN.TVC: Generate simulation data to test time-dependent Cox model...

In michaelyanwang/dcalasso: Divide-and-conquer adaptive lasso for big data

Description

SIM.FUN.TVC generates time-dependent survival response with four time-intervals 0-1, 1-2, 2-3, 3-4 for each subject data. All subjects are administratively censored at 4, if T>4. T comes from a Weibull distribution with shape of 2. The design matrix comes from a correlated multivariate normal. The default signals (beta0) are sparse.

Usage

SIM.FUN.TVC(p.ti = 50, p.tv = 50, n.subject = 1e+06, cor = 0.2,
  beta0.ti = NULL, beta0.tv = NULL)

Arguments

p.ti	number of time-invariant covariates
p.tv	number of time-varying covariates
n.subject	number of subjects
cor	correlation between time-varying and each interval's time-varying covairates
beta.ti	coefficient for time-invariant covariates
beta.tv	coefficients for time-varying covariates

Value

a matrix with the first column starting time, second column ending time, third column event (0,1), and rest = design matrix + ID for subject.

Author(s)

Yan Wang, Tianxi Cai, Chuan Hong

References

Section 3.3 in Austin, P.C., 2012. Generating survival times to simulate Cox proportional hazards models with time‐varying covariates. Statistics in medicine, 31(29), pp.3946-3958.

Examples

SIM.FUN.tvc()

michaelyanwang/dcalasso documentation built on Nov. 22, 2019, 3:51 a.m.