mHP.b: Compute the efficacy boundary (modified Haybittle-Peto) for...
In bnaras/ASSISTant: Adaptive Subgroup Selection in Group Sequential Trials

Compute the efficacy boundary (modified Haybittle-Peto) for the first two stages

1	mHP.b(prevalence, N, cov.J, mu.prime, Sigma.prime, alpha, btilde, theta)

`prevalence`	the vector of prevalences between 0 and 1 summing to 1. J, the number of groups, is implicitly the length of this vector and should be at least 2.
`N`	a three-vector of total sample size at each stage
`cov.J`	the 3 x 3 covariance matrix for Z_J at each of the three stages
`mu.prime`	a list of J mean vectors, each of length J-1 representing the conditional means of all the other Z_j given Z_i. This mean does not account for the conditioned value of Z_i and so has to be multiplied by that during use!
`Sigma.prime`	a list of J covariance matrices, each J-1 by J-1 representing the conditional covariances all the other Z_j given Z_i
`alpha`	the amount of type I error to spend
`btilde`	the futility boundary
`theta`	the effect size on the probability scale

Adaptive Choice of Patient Subgroup for Comparing Two Treatments by Tze Leung Lai and Philip W. Lavori and Olivia Yueh-Wen Liao. Contemporary Clinical Trials, Vol. 39, No. 2, pp 191-200 (2014). http://www.sciencedirect.com/science/article/pii/S1551714414001311

bnaras/ASSISTant documentation built on Nov. 23, 2019, 6:20 p.m.