View source: R/simulatetrials.R
This function doesn't use an actual second point, just the projected based on the initial point simulate.trials <- function(n1=20, N1=200, N=200, n.trt=3, mean.s=rep(0,3), mean.t=rep(0,3), p1, sigma0=1, sigma=1, rho=0.0, nsim=1000, save.boundary, simonly=0)
1 2 3 | simulateest(n1 = 20, N1 = 100, N = 200, n.trt = 3, mean.s = NULL,
mean.t = NULL, p1, p2, sigma0, sigma, rho, nsim, design = "Pocock",
tau1, tau2, save.boundary)
|
N1 |
Number of patients with secondary endpoint available at first analysis |
N |
The total number of patients in the trial |
n.trt |
The number of treatments in the trial |
mean.s |
The mean for short term endpoint sample groups |
mean.t |
Mean for the long term endpoint sample groups |
p1 |
The covariate value for the first covariate |
p2 |
THe covariate value for the second covariate |
sigma0 |
sigma0 in the bivariate normal distribution |
sigma |
is the known sigma for the population |
rho |
is the known correlation between endpoints. |
nsim |
The number of simulation runs. The default is 1000 |
design |
The chosen covariate adaptive randomization procedure. Default is Pocock's design |
tau1 |
The chosen covariate adaptive randomization procedure. Default is Pocock's design |
tau2 |
The chosen covariate adaptive randomization procedure. Default is Pocock's design |
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