Analysis Results Inverse Normal

Description

Class for analysis results results based on an inverse normal design.

Details

This object cannot be created directly; use getAnalysisResults with suitable arguments to create the analysis results of a inverse normal 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.