SimulationResultsMultiArmMeans: Class for Simulation Results Multi-Arm Means
In rpact: Confirmatory Adaptive Clinical Trial Design and Analysis

SimulationResultsMultiArmMeans

R Documentation

Class for Simulation Results Multi-Arm Means

Description

A class for simulation results means in multi-arm designs.

Details

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

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.
stDev: The standard deviation used for sample size and power calculation. Is a numeric 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.
minNumberOfSubjectsPerStage: Determines the minimum number of subjects per stage for data-driven sample size recalculation. For two treatment arms, is the number of subjects for both treatment arms. For multi-arm designs, is the minimum number of subjects per selected active arm. Is a numeric vector of length kMax containing whole numbers.
maxNumberOfSubjectsPerStage: Determines the maximum number of subjects per stage for data-driven sample size recalculation. For two treatment arms, is the number of subjects for both treatment arms. For multi-arm designs, is the minimum number of subjects per selected active arm. Is a numeric vector of length kMax containing whole numbers.
thetaH1: The assumed effect under the alternative hypothesis. For survival designs, refers to the hazard ratio. Is a numeric vector.
stDevH1: The standard deviation under which the conditional power or sample size recalculation is performed. Is a numeric vector of length 1.
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.
activeArms: The number of active treatment arms to be compared with control. Is a numeric vector of length 1 containing a whole number.
effectMatrix: The matrix of effect sizes with activeArms columns and number of rows reflecting the different situations to consider.
typeOfShape: The shape of the dose-response relationship over the treatment groups. Is a character vector of length 1.
muMaxVector: The range of effect sizes for the treatment group with highest response for "linear" and "sigmoidEmax" model. Is a numeric vector.
gED50: The ED50 of the sigmoid Emax model. Only necessary if typeOfShape = "sigmoidEmax" has been specified. Is a numeric vector of length 1.
slope: The slope of the sigmoid Emax model, if typeOfShape = "sigmoidEmax" Is a numeric vector of length 1.
intersectionTest: The multiple test used for intersection hypotheses in closed systems of hypotheses. Is a character vector of length 1.
adaptations: Indicates whether or not an adaptation takes place at interim k. Is a logical vector of length kMax minus 1.
typeOfSelection: The way the treatment arms or populations are selected at interim. Is a character vector of length 1.
effectMeasure: Criterion for treatment arm/population selection, either based on test statistic ("testStatistic") or effect estimate ("effectEstimate"). Is a character vector of length 1.
successCriterion: Defines when the study is stopped for efficacy at interim. "all" stops the trial if the efficacy criterion has been fulfilled for all selected treatment arms/populations, "atLeastOne" stops if at least one of the selected treatment arms/populations is shown to be superior to control at interim. Is a character vector of length 1.
epsilonValue: Needs to be specified if typeOfSelection = "epsilon". Is a numeric vector of length 1.
rValue: Needs to be specified if typeOfSelection = "rBest". Is a numeric vector of length 1.
threshold: The selection criterion: treatment arm/population is only selected if effectMeasure exceeds threshold. Either a single numeric value or a numeric vector of length activeArms referring to a separate threshold condition for each treatment arm.
selectArmsFunction: An optional function that can be entered to define how treatment arms are selected.
earlyStop: The probability to stopping the trial either for efficacy or futility. Is a numeric vector.
selectedArms: The selected arms in multi-armed designs.
numberOfActiveArms: The number of active arms in a multi-armed design. Is a numeric matrix.
rejectAtLeastOne: The probability to reject at least one of the (multiple) hypotheses. Is a numeric vector.
rejectedArmsPerStage: The simulated number of rejected arms per stage.
successPerStage: The simulated success probabilities per stage where success is defined by user. Is a numeric matrix.
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.
conditionalPowerAchieved: The calculated conditional power, under the assumption of observed or assumed effect sizes. Is a numeric matrix.