blindrecalc: adjusted_alpha.FarringtonManning – R documentation

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adjusted_alpha.FarringtonManning

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 'FarringtonManning'
adjusted_alpha(
  design,
  n1,
  nuisance,
  nuis_ass,
  precision = 0.001,
  gamma = 0,
  recalculation,
  allocation = c("exact", "approximate"),
  ...
)

Arguments

`design`	Object of class `FarringtonManning` created by `setupFarringtonManning`.
`n1`	Either the sample size of the first stage (if `recalculation = TRUE` or the toal sample size (if `recalculation = FALSE`).
`nuisance`	Value of the nuisance parameter. For the Farrington-Manning 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 recalcuated after n1 patients are recruited?
`allocation`	Whether the allocation ratio should be preserved exactly (`exact`) or approximately (`approximate`).
`...`	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 <- setupFarringtonManning(alpha = 0.025, beta = 0.2, r = 1, delta = 0, delta_NI = 0.25)
adjusted_alpha(d, n1 = 20, nuisance = 0.5, recalculation = TRUE)

blindrecalc

Blinded Sample Size Recalculation

v0.1.2

MIT + file LICENSE

Authors

Lukas Baumann [aut], Maximilian Pilz [aut, cre], Institute of Medical Biometry and Informatics - University of Heidelberg [cph]

Initial release