getRepeatedPValues {rpact} | R Documentation |
Calculates the repeated p-values for a given test results.
getRepeatedPValues(stageResults, ..., tolerance = 1e-06)
stageResults |
The results at given stage, obtained from |
... |
Ensures that all arguments (starting from the "...") are to be named and that a warning will be displayed if unknown arguments are passed. |
tolerance |
The numerical tolerance, default is |
The repeated p-value at a given stage of the trial is defined as the smallest significance level under which at given test design the test results obtain rejection of the null hypothesis. It can be calculated at each stage of the trial and can thus be used as a monitoring tool.
The repeated p-values are provided up to the specified stage.
In multi-arm trials, the repeated p-values are defined separately for each treatment comparison within the closed testing procedure.
Returns a numeric
vector of length kMax
or in case of multi-arm stage results
a matrix
(each column represents a stage, each row a comparison)
containing the repeated p values.
mnormt
If intersectionTest = "Dunnett"
or intersectionTest = "SpiessensDebois"
, or the design is a conditional Dunnett design and
the dataset is a multi-arm or enrichment dataset, rpact
uses the R package mnormt
to calculate the analysis results.
Other analysis functions:
getAnalysisResults()
,
getClosedCombinationTestResults()
,
getClosedConditionalDunnettTestResults()
,
getConditionalPower()
,
getConditionalRejectionProbabilities()
,
getFinalConfidenceInterval()
,
getFinalPValue()
,
getRepeatedConfidenceIntervals()
,
getStageResults()
,
getTestActions()
## Not run:
design <- getDesignInverseNormal(kMax = 2)
data <- getDataset(
n = c( 20, 30),
means = c( 50, 51),
stDevs = c(130, 140)
)
getRepeatedPValues(getStageResults(design, dataInput = data))
## End(Not run)