adjusted_alpha,ChiSquare-method {blindrecalc}

Adjusted level of significance

Description

This method returns an adjusted significance level that can be used such that the actual type I error rate is preserved.

Usage

## S4 method for signature 'ChiSquare'
adjusted_alpha(
  design,
  n1,
  nuisance,
  nuis_ass,
  precision = 0.001,
  gamma = 0,
  recalculation,
  allocation = c("exact", "approximate"),
  ...
)

Arguments

design

Object of class ChiSquare created by setupChiSquare.

n1

Either the sample size of the first stage (if recalculation = TRUE or the total sample size (if recalculation = FALSE).

nuisance

Value of the nuisance parameter in (0,1). For the Chi-Squared test this is the overall response rate.

nuis_ass

If recalculation = FALSE this is the value for the overall response rate that is used to calculate the sample size for the adjusted significance level.

precision

Value by which the nominal type 1 error rate is reduced in each iteration until the nominal type 1 error rate is preserved.

gamma

If gamma > 0 then the significance level is adjusted such that the actual level is at most alpha - gamma. This is necessary to maintain the nomininal significance level if a confidence interval approach proposed by Friede & Kieser (2011) is used.

recalculation

Should the sample size be recalculated after n1 n1 patients are recruited?

allocation

Whether the allocation ratio should be preserved exactly (exact) or approximately (approximate or kf_approx). appproximate uses the unrounded calculated sample size in the sample size recalculation, kf_approx rounds the sample size to the next integer.

...

Further optional arguments.

Details

The method is only vectorized in either nuisance or n1.

Value

Value of the adjusted significance level for every nuisance parameter and every value of n1.

Examples

  d <- setupChiSquare(alpha = 0.025, beta = 0.2, r = 1, delta = 0.2)
  adjusted_alpha(d, n1 = 10, nuisance = 0.3, gamma = 0.001,
     nuis_ass = 0.3, precision = 0.001, recalculation = TRUE)