getConditionalRejectionProbabilities {rpact}  R Documentation 
Calculates the conditional rejection probabilities (CRP) for given test results.
getConditionalRejectionProbabilities(stageResults, ...)
stageResults 
The results at given stage, obtained from 
... 
Further (optional) arguments to be passed:

The conditional rejection probability is the probability, under H0, to reject H0 in one of the subsequent (remaining) stages. The probability is calculated using the specified design. For testing rates and the survival design, the normal approximation is used, i.e., it is calculated with the use of the prototype case testing a mean for normally distributed data with known variance.
The conditional rejection probabilities are provided up to the specified stage.
For Fisher's combination test, you can check the validity of the CRP calculation via simulation.
Returns a numeric
vector of length kMax
or in case of multiarm stage results
a matrix
(each column represents a stage, each row a comparison)
containing the conditional rejection probabilities.
Other analysis functions:
getClosedCombinationTestResults()
,
getClosedConditionalDunnettTestResults()
,
getConditionalPower()
,
getFinalConfidenceInterval()
,
getFinalPValue()
,
getRepeatedConfidenceIntervals()
,
getRepeatedPValues()
,
getStageResults()
,
getTestActions()
## Not run:
# Calculate CRP for a Fisher's combination test design with
# two remaining stages and check the results by simulation.
design < getDesignFisher(kMax = 4,
informationRates = c(0.1, 0.3, 0.8, 1), alpha = 0.01)
data < getDataset(n = c(40, 40), events = c(20, 22))
sr < getStageResults(design, data, thetaH0 = 0.4)
getConditionalRejectionProbabilities(sr)
getConditionalRejectionProbabilities(sr, simulateCRP = TRUE,
seed = 12345, iterations = 10000)
## End(Not run)