Calculate the factor which relates \(\alpha_2\) to the second-stage information for given conditional power.
Usage
getNu(alpha, conditionalPower)
Value
Factor linking information and \(\alpha_2\).
Arguments
alpha
The (conditional) type I error rate of the design. Must be a numeric vector with values between 0 and 1.
conditionalPower
The target conditional power \(CP\) of the design. Must be a numeric value.
Details
Note that this function uses factor 1 instead of factor 2 (Brannath & Bauer 2004). This has no impact on the optimal conditional error function, as constant factors are absorbed by the level constant \(c_0\).
The calculation is:
$$\nu(\alpha_2(p_1)) = (\Phi^{-1}(1-\alpha_2(p_1)) + \Phi^{-1}(CP))^2.$$
References
Brannath, W. & Bauer, P. (2004). Optimal conditional error functions for the control of conditional power. Biometrics. https://www.jstor.org/stable/3695393