BuyseTest (version 1.8.5)

powerBuyseTest: Performing simulation studies with BuyseTest

Description

Performs a simulation studies for several sample sizes. Returns estimates, standard errors, confidence intervals and p.values.

Usage

powerBuyseTest(sim, sample.size, sample.sizeC = NULL,
  sample.sizeT = NULL, n.rep, null = c(0, 1), cpus = 1, seed = 10,
  conf.level = NULL, order.Hprojection = NULL, transformation = NULL,
  trace = 1, ...)

Arguments

sim

[function] take two arguments: the sample size in the control group (n.C) and the sample size in the treatment group (n.C) and generate datasets. The datasets must be data.table objects.

sample.size

[integer vector, >0] the various sample sizes at which the simulation should be perform. Disregarded if any of the arguments sample.sizeC or sample.sizeT are specified.

sample.sizeC

[integer vector, >0] the various sample sizes in the control group.

sample.sizeT

[integer vector, >0] the various sample sizes in the treatment group.

n.rep

[integer, >0] the number of simulations.

null

[numeric vector] the null hypothesis to be tested for the net benefit (first element) and the win ratio (second element).

cpus

[integer, >0] the number of CPU to use. Only the permutation test can use parallel computation. Default value read from BuyseTest.options().

seed

[integer, >0] the seed to consider for the simulation study.

conf.level

[numeric] confidence level for the confidence intervals. Default value read from BuyseTest.options().

order.Hprojection

[integer 1,2] the order of the H-project to be used to compute the variance of the net benefit/win ratio.

transformation

[logical] should the CI be computed on the logit scale / log scale for the net benefit / win ratio and backtransformed. Otherwise they are computed without any transformation. Default value read from BuyseTest.options().

trace

[integer] should the execution of the function be traced?

...

parameters from BuyseTest.

Examples

# NOT RUN {
library(data.table)

## using simBuyseTest
powerBuyseTest(sim = simBuyseTest, sample.size = c(100), n.rep = 2,
               formula = treatment ~ bin(toxicity),
               method.inference = "u-statistic", trace = 4)

## using user defined simulation function
simFCT <- function(n.C, n.T){
    out <- data.table(Y=rnorm(n.C+n.T),
                      T=c(rep(1,n.C),rep(0,n.T))
                     )
return(out)
}

powerBuyseTest(sim = simFCT, sample.size = c(100), n.rep = 2,
              formula = T ~ cont(Y), method.inference = "u-statistic", trace = 4)

# }