Analysis Results Group Sequential
Source:R/class_analysis_results.R
AnalysisResultsGroupSequential.Rd
Class for analysis results results based on a group sequential design.
Details
This object cannot be created directly; use getAnalysisResults
with suitable arguments to create the analysis results of a group sequential design.
Fields
normalApproximation
Describes if a normal approximation was used when calculating p-values. Default for means is
FALSE
andTRUE
for rates and hazard ratio. Is a logical vector of length 1.directionUpper
Specifies the direction of the alternative, only applicable for one-sided testing. Default is
TRUE
which means that larger values of the test statistics yield smaller p-values. Is a logical vector of length 1.thetaH0
The difference or assumed effect under H0. Is a numeric vector of length 1.
pi1
The assumed probability or probabilities in the active treatment group in two-group designs, or the alternative probability for a one-group design.
pi2
The assumed probability in the reference group for two-group designs. Is a numeric vector of length 1 containing a value between 0 and 1.
nPlanned
The sample size planned for each of the subsequent stages. Is a numeric vector of length
kMax
containing whole numbers.allocationRatioPlanned
The planned allocation ratio (
n1 / n2
) for the groups. For multi-arm designs, it is the allocation ratio relating the active arm(s) to the control. Is a positive numeric vector of length 1.thetaH1
The assumed effect under the alternative hypothesis. For survival designs, refers to the hazard ratio. Is a numeric vector.
assumedStDev
The assumed standard deviation(s) for means analysis. Is a numeric vector.
equalVariances
Describes if the variances in two treatment groups are assumed to be the same. Is a logical vector of length 1.
testActions
The test decisions at each stage of the trial. Is a character vector of length
kMax
.conditionalRejectionProbabilities
The probabilities of rejecting the null hypothesis at each stage, given the stage has been reached. Is a numeric vector of length
kMax
containing values between 0 and 1.conditionalPower
The conditional power at each stage of the trial. Is a numeric vector of length 1 containing a value between 0 and 1.
repeatedConfidenceIntervalLowerBounds
The lower bound of the confidence intervals that are calculated at any stage of the trial. Is a numeric vector of length
kMax
.repeatedConfidenceIntervalUpperBounds
The upper bound of the confidence interval that are calculated at any stage of the trial. Is a numeric vector of length
kMax
.repeatedPValues
The p-values that are calculated at any stage of the trial. Is a numeric vector of length
kMax
containing values between 0 and 1.finalStage
The stage at which the trial ends, either with acceptance or rejection of the null hypothesis. Is a numeric vector of length 1.
finalPValues
The final p-value that is based on the stage-wise ordering. Is a numeric vector of length
kMax
containing values between 0 and 1.finalConfidenceIntervalLowerBounds
The lower bound of the confidence interval that is based on the stage-wise ordering. Is a numeric vector of length
kMax
.finalConfidenceIntervalUpperBounds
The upper bound of the confidence interval that is based on the stage-wise ordering. Is a numeric vector of length
kMax
.medianUnbiasedEstimates
The calculated median unbiased estimates that are based on the stage-wise ordering. Is a numeric vector of length
kMax
.maxInformation
The maximum information. Is a numeric vector of length 1 containing a whole number.
informationEpsilon
The absolute information epsilon, which defines the maximum distance from the observed information to the maximum information that causes the final analysis. Updates at the final analysis if the observed information at the final analysis is smaller ("under-running") than the planned maximum information. Is either a positive integer value specifying the absolute information epsilon or a floating point number >0 and <1 to define a relative information epsilon.