get_initial_design: Initial design

In kkmann/adoptr: Adaptive Optimal Two-Stage Designs in R

Initial design

Description

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.

Usage

get_initial_design(
  theta,
  alpha,
  beta,
  type = c("two-stage", "group-sequential", "one-stage"),
  dist = Normal(),
  order = 7L,
  ...
)

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

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
)

kkmann/adoptr documentation built on Feb. 3, 2024, 6:55 p.m.