mHP.btilde: Compute the futility boundary (modified Haybittle-Peto) for...
In ASSISTant: Adaptive Subgroup Selection in Group Sequential Trials
mHP.btilde R Documentation
Compute the futility boundary (modified Haybittle-Peto) for the
first two stages
Description
The futility boundary btilde is computed by
solving (under the alternative)
Usage
mHP.btilde(beta, cov.J)
Arguments
beta
the type II error
cov.J
the 3 x 3 covariance matrix
Details
P(\tilde{Z}_J^1≤\tilde{b} or \tilde{Z}_J^2≤\tilde{b}) = εβ
where the superscripts denote the stage and ε is the
fraction of the type I error (α) spent and β
is the type II error. We make use of the joint normal density of
Z_{J} (the overall group) at each of the three stages and the
fact that the \tilde{Z_J} is merely a translation of
Z_J. So here the calculation is based on a mean of zero and
has to be translated during use!
ASSISTant documentation built on Dec. 2, 2022, 5:12 p.m.
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| mHP.btilde | R Documentation |
Compute the futility boundary (modified Haybittle-Peto) for the first two stages
Description
The futility boundary btilde is computed by solving (under the alternative)
Usage
mHP.btilde(beta, cov.J)
Arguments
beta |
the type II error |
cov.J |
the 3 x 3 covariance matrix |
Details
P(\tilde{Z}_J^1≤\tilde{b} or \tilde{Z}_J^2≤\tilde{b}) = εβ
where the superscripts denote the stage and ε is the fraction of the type I error (α) spent and β is the type II error. We make use of the joint normal density of Z_{J} (the overall group) at each of the three stages and the fact that the \tilde{Z_J} is merely a translation of Z_J. So here the calculation is based on a mean of zero and has to be translated during use!
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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