Analysis Results Group Sequential

Description

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 and TRUE 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.