Class for analysis results based on a Fisher combination test design.
Details
This object cannot be created directly; use getAnalysisResults
with suitable arguments to create the analysis results of a Fisher combination test 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
.conditionalPowerSimulated
The simulated conditional power, under the assumption of observed or assumed effect sizes.
iterations
The number of iterations used for simulations. Is a numeric vector of length 1 containing a whole number.
seed
The seed used for random number generation. Is a numeric vector of length 1.