computeMHPBoundaryITT: Compute the three modified Haybittle-Peto boundaries and...
In bnaras/ASSISTant: Adaptive Subgroup Selection in Group Sequential Trials
Description
Usage
Arguments
Value
References
Description
Compute the three modified Haybittle-Peto boundaries and effect size
Usage
1
computeMHPBoundaryITT(prevalence, alpha)
Arguments
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.
alpha
the type I error
Value
a named vector of a single value containing the value for c
References
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.
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Description Usage Arguments Value References
Description
Compute the three modified Haybittle-Peto boundaries and effect size
Usage
1 | computeMHPBoundaryITT(prevalence, alpha)
|
Arguments
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. |
alpha |
the type I error |
Value
a named vector of a single value containing the value for c
References
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
R Package Documentation
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