sim_BSSRed: Simulation
In Knusprikus/BSSRed: Blinded Sample Size Reestimation For Event Driven Trials

Simulation

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sim_BSSRed(N, tn, M, tm, addRecT, sim.lambdaP, sigma=1, theta.star, gamma, kappa=1,
           distS=c("exponential","weibull"), distC=c("exponential","weibull"),
           nEvents, L, nSim=100, par.est=FALSE, fixed.min.studytime=TRUE, seed=235711)

`addRecT`	a vector defining the allowed additional recruitment batches.
`sigma`	a number defining the shape parameter of the survival prozess.
`theta.star`	a number defining the true hazard ratio.
`gamma`	a number defining the hazard of the censor process.
`kappa`	a number defining the shape parameter of the censor prozess.
`distS`	a string defining the distribution of the survival process. Default is `"exponential"`.
`distC`	a string defining the distribution of the censor process. Default is `"exponential"`.
`nEvents`	a number defining the targeted number of events. (alternatively alpha, beta)
`L`	a number defining the administrative censoring time.
`nSim`	a number defining the number of simulations per parametrisation.
`par.est`	a boolean. If `TRUE` the parameter-estimates and teststatistik will be calculated. Warning: will greatliy increase runtime.
`fixed.min.studytime`	a boolean. If `TRUE` the simulated studies will not stop before `L`. If `FALSE` the study will end when the targeted amount of events is reached.
`seed`	a number defining the seed.
`N`	a two-column matrix which represents the size of recruitment per group.
`tn`	a vector of length `NROW(N)` defining the timepoint of each recruitment-batch.
`M`	a matrix defining the ongoining recruitment after the planned N. Default is the last row of N.
`tm`	a vector of length `NROW(M)` defining the timepoint of each future recruitment-batch. Default is the next equidistant timepoint after the last of `tn`.
`sim.lambdaP`	a vector defining the hazard rates of the control group.