simBivRec {BivRec}  R Documentation 
This function simulates a series of alternating recurrent events based on the simulation setting in Lee, Huang, Xu, Luo (2018).
simBivRec(nsize, beta1, beta2, tau_c, set)
nsize 
Sample size which refers to the number of subjects in the data set where each subject could have multiple episodes of events. 
beta1 
True coefficients for Type I gap times in the accelerated failure time model (AFT). 
beta2 
True coefficients for Type II gap times in the accelerated failure time model (AFT). 
tau_c 
Maximum support of censoring time. It can take values as follows:

set 
Simulation setting based on scenarios outlined in Tables 1 and 2 in Lee, Huang, Xu, Luo (2018). Choose 1.1 (default) for scenario 1 with ρ=1 in the covariance matrix of the frailty vector, 1.2 for scenario 1 with ρ=0.5, 1.3 for scenario 1 with ρ=0 and 2.0 for scenario 2. 
Data frame with the alternating recurrent event data and one continuous and one binary covariate.
Lee CH, Huang CY, Xu G, Luo X. (2018). Semiparametric regression analysis for alternating recurrent event data. Statistics in Medicine, 37: 9961008. doi: 10.1002/sim.7563
library(BivRec) set.seed(1234) sim_data < simBivRec(nsize=150, beta1=c(0.5,0.5), beta2=c(0,0.5), tau_c=63, set=1.1) head(sim_data)