PValueclass {adestr}  R Documentation 
Pvalues
Description
This is the parent class for all pvalues implemented in this package. Details about the methods for calculating pvalues can be found in (our upcoming paper).
Usage
PValue(g1, g2, label)
LinearShiftRepeatedPValue(wc1f = 0, wc1e = 1/2, wc2 = 1/2)
MLEOrderingPValue()
LikelihoodRatioOrderingPValue()
ScoreTestOrderingPValue()
StagewiseCombinationFunctionOrderingPValue()
NeymanPearsonOrderingPValue(mu0 = 0, mu1 = 0.4)
Arguments
g1 
functional representation of the pvalue in the early futility and efficacy regions. 
g2 
functional representation of the pvalue in the continuation region. 
label 
name of the pvalue. Used in printing methods. 
wc1f 
slope of futility boundary change. 
wc1e 
slope of efficacy boundary change. 
wc2 
slope of c2 boundary change. 
mu0 
expected value of the normal distribution under the null hypothesis. 
mu1 
expected value of the normal distribution under the null hypothesis. 
Details
The implemented pvalues are:

MLEOrderingPValue()

LikelihoodRatioOrderingPValue()

ScoreTestOrderingPValue()

StagewiseCombinationFunctionOrderingPValue()
The pvalues are calculated by specifying an ordering of the sample space calculating the probability that a random sample under the null hypothesis is larger than the observed sample. Some of the implemented orderings are based on the work presented in (Emerson and Fleming 1990), (Sections 8.4 in Jennison and Turnbull 1999), and (Sections 4.1.1 and 8.2.1 in Wassmer and Brannath 2016).
Value
an object of class PValue
. This class signals that an
object can be supplied to the analyze
function.
References
Emerson SS, Fleming TR (1990).
“Parameter estimation following group sequential hypothesis testing.”
Biometrika, 77(4), 875–892.
doi:10.2307/2337110.
Jennison C, Turnbull BW (1999).
Group Sequential Methods with Applications to Clinical Trials, 1 edition.
Chapman and Hall/CRC., New York.
doi:10.1201/9780367805326.
Wassmer G, Brannath W (2016).
Group Sequential and Confirmatory Adaptive Designs in Clinical Trials, 1 edition.
Springer, Cham, Switzerland.
doi:10.1007/9783319325620.
See Also
Examples
# This is the definition of a 'naive' pvalue based on a Ztest for a onearmed trial
PValue(
g1 = \(smean1, n1, sigma, ...) pnorm(smean1*sqrt(n1)/sigma, lower.tail=FALSE),
g2 = \(smean1, smean2, n1, n2, ...) pnorm((n1 * smean1 + n2 * smean2)/(n1 + n2) *
sqrt(n1+n2)/sigma, lower.tail=FALSE),
label="My custom pvalue")