SimulationResultsRates: Class for Simulation Results Rates
In rpact: Confirmatory Adaptive Clinical Trial Design and Analysis

SimulationResultsRates

R Documentation

Class for Simulation Results Rates

Description

A class for simulation results rates.

Details

Use getSimulationRates() to create an object of this type.

SimulationResultsRates is the basic class for

SimulationResultsRates,
SimulationResultsMultiArmRates, and
SimulationResultsEnrichmentRates.

Fields

maxNumberOfIterations: The number of simulation iterations. 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.
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.
conditionalPower: The conditional power at each stage of the trial. Is a numeric vector of length 1 containing a value between 0 and 1.
iterations: The number of iterations used for simulations. Is a numeric vector of length 1 containing a whole number.
futilityPerStage: The per-stage probabilities of stopping the trial for futility. Is a numeric matrix.
futilityStop: In simulation results data set: indicates whether trial is stopped for futility or not.
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.
plannedSubjects: Determines the number of cumulated (overall) subjects when the interim stages are planned. For two treatment arms, is the number of subjects for both treatment arms. For multi-arm designs, refers to the number of subjects per selected active arm. Is a numeric vector of length kMax containing whole numbers.
maxNumberOfSubjects: The maximum number of subjects for power calculations. Is a numeric vector.
calcSubjectsFunction: An optional function that can be entered to define how sample size is recalculated. By default, recalculation is performed with conditional power with specified minNumberOfSubjectsPerStage and maxNumberOfSubjectsPerStage.
expectedNumberOfSubjects: The expected number of subjects under specified alternative.
riskRatio: Specifies if the sample size for one-sided testing of H0: pi1 / pi2 = thetaH0 has been calculated. Is a logical vector of length 1.
thetaH0: The difference or assumed effect under H0. Is a numeric vector of length 1.
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.
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.
groups: The group numbers. Is a numeric vector.
pi1H1: The assumed probability in the active treatment group for two-group designs, or the assumed probability for a one treatment group design, for which the conditional power was calculated. Is a numeric vector of length 1 containing a value between 0 and 1.
pi2H1: The assumed probability in the reference group for two-group designs, for which the conditional power was calculated. Is a numeric vector of length 1 containing a value between 0 and 1.
effect: The effect for randomly creating normally distributed responses. Is a numeric vector of length kMax.
earlyStop: The probability to stopping the trial either for efficacy or futility. Is a numeric vector.
sampleSizes: The sample sizes for each group and stage. Is a numeric vector of length number of stages times number of groups containing whole numbers.
overallReject: The overall rejection probability. Is a numeric vector.
rejectPerStage: The probability to reject a hypothesis per stage of the trial. Is a numeric matrix.
conditionalPowerAchieved: The calculated conditional power, under the assumption of observed or assumed effect sizes. Is a numeric matrix.