adjusted_alpha {blindrecalc} | R Documentation |

## 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

```
adjusted_alpha(design, n1, nuisance, ...)
```

### Arguments

`design` |
object of class |

`n1` |
total number of patients that are recruited before the sample size is recalculated |

`nuisance` |
nuisance parameter that is estimated at the interim analysis |

`...` |
Further optional arguments. |

### Details

The method is only vectorized in either `nuisance`

or `n1`

.

The method is implemented for the classes `Student`

,
`ChiSquare`

, and `FarringtonManning`

.
Check the class-specific documentation for further parameters that have
to be specified.

### Value

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

### Examples

```
d <- setupStudent(alpha = .025, beta = .2, r = 1, delta = 0, delta_NI = 1.5, n_max = 848)
sigma <- c(2, 5.5, 9)
adjusted_alpha(design = d, n1 = 20, nuisance = sigma, tol = 1e-4, iters = 1e3)
```

[Package

*blindrecalc*version 1.0.1 Index]