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
normalApproximationDescribes if a normal approximation was used when calculating p-values. Default for means is
FALSEandTRUEfor rates and hazard ratio. Is a logical vector of length 1.directionUpperSpecifies the direction of the alternative, only applicable for one-sided testing. Default is
TRUEwhich means that larger values of the test statistics yield smaller p-values. Is a logical vector of length 1.thetaH0The difference or assumed effect under H0. Is a numeric vector of length 1.
pi1The assumed probability or probabilities in the active treatment group in two-group designs, or the alternative probability for a one-group design.
pi2The assumed probability in the reference group for two-group designs. Is a numeric vector of length 1 containing a value between 0 and 1.
nPlannedThe sample size planned for each of the subsequent stages. Is a numeric vector of length
kMaxcontaining whole numbers.allocationRatioPlannedThe 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.thetaH1The assumed effect under the alternative hypothesis. For survival designs, refers to the hazard ratio. Is a numeric vector.
assumedStDevThe assumed standard deviation(s) for means analysis. Is a numeric vector.
equalVariancesDescribes if the variances in two treatment groups are assumed to be the same. Is a logical vector of length 1.
testActionsThe test decisions at each stage of the trial. Is a character vector of length
kMax.conditionalRejectionProbabilitiesThe probabilities of rejecting the null hypothesis at each stage, given the stage has been reached. Is a numeric vector of length
kMaxcontaining values between 0 and 1.conditionalPowerThe conditional power at each stage of the trial. Is a numeric vector of length 1 containing a value between 0 and 1.
repeatedConfidenceIntervalLowerBoundsThe lower bound of the confidence intervals that are calculated at any stage of the trial. Is a numeric vector of length
kMax.repeatedConfidenceIntervalUpperBoundsThe upper bound of the confidence interval that are calculated at any stage of the trial. Is a numeric vector of length
kMax.repeatedPValuesThe p-values that are calculated at any stage of the trial. Is a numeric vector of length
kMaxcontaining values between 0 and 1.finalStageThe stage at which the trial ends, either with acceptance or rejection of the null hypothesis. Is a numeric vector of length 1.
finalPValuesThe final p-value that is based on the stage-wise ordering. Is a numeric vector of length
kMaxcontaining values between 0 and 1.finalConfidenceIntervalLowerBoundsThe lower bound of the confidence interval that is based on the stage-wise ordering. Is a numeric vector of length
kMax.finalConfidenceIntervalUpperBoundsThe upper bound of the confidence interval that is based on the stage-wise ordering. Is a numeric vector of length
kMax.medianUnbiasedEstimatesThe calculated median unbiased estimates that are based on the stage-wise ordering. Is a numeric vector of length
kMax.conditionalPowerSimulatedThe simulated conditional power, under the assumption of observed or assumed effect sizes.
iterationsThe number of iterations used for simulations. Is a numeric vector of length 1 containing a whole number.
seedThe seed used for random number generation. Is a numeric vector of length 1.
