computeBetaSafeT {safestats} | R Documentation |
Helper function: Computes the type II error of the safeTTest based on the minimal clinically relevant standardised mean difference and nPlan.
Description
Helper function: Computes the type II error of the safeTTest based on the minimal clinically relevant standardised mean difference and nPlan.
Usage
computeBetaSafeT(
deltaMin,
nPlan,
alpha = 0.05,
alternative = c("twoSided", "greater", "less"),
testType = c("oneSample", "paired", "twoSample"),
seed = NULL,
parameter = NULL,
pb = TRUE,
nSim = 1000L,
nBoot = 1000L
)
Arguments
deltaMin |
numeric that defines the minimal relevant standardised effect size, the smallest effect size that we would the experiment to be able to detect. |
nPlan |
vector of max length 2 representing the planned sample sizes. |
alpha |
numeric in (0, 1) that specifies the tolerable type I error control –independent of n– that the designed test has to adhere to. Note that it also defines the rejection rule e10 > 1/alpha. |
alternative |
a character string specifying the alternative hypothesis must be one of "twoSided" (default), "greater" or "less". |
testType |
either one of "oneSample", "paired", "twoSample". |
seed |
integer, seed number. |
parameter |
optional test defining parameter. Default set to |
pb |
logical, if |
nSim |
integer > 0, the number of simulations needed to compute power or the number of samples paths for the safe z test under continuous monitoring. |
nBoot |
integer > 0 representing the number of bootstrap samples to assess the accuracy of approximation of the power, the number of samples for the safe z test under continuous monitoring, or for the computation of the logarithm of the implied target. |
Value
a list which contains at least beta and an adapted bootObject of class
boot
.
Examples
computeBetaSafeT(deltaMin=0.7, 27, nSim=10)