The optimization method minimize
requires an initial
design for optimization.
The function get_initial_design
provides an initial guess based on a
fixed design that fulfills constraints on type I error rate and power.
Note that a situation-specific initial design may be much more efficient.
Arguments
- theta
the alternative effect size in the normal case, the rate difference under the alternative in the binomial case
- alpha
maximal type I error rate
- beta
maximale type II error rate
- type
is a two-stage, group-sequential, or one-stage design requried?
- dist
distribution of the test statistic
- order
desired integration order
- ...
further optional arguments
Value
An object of class TwoStageDesign
.
Details
The distribution of the test statistic is specified by dist
.
The default assumes a two-armed z-test.
Examples
init <- get_initial_design(
theta = 0.3,
alpha = 0.025,
beta = 0.2,
type = "two-stage",
dist = Normal(two_armed = FALSE),
order = 7L
)