rpact (version 3.4.0)

getPerformanceScore: Get Performance Score

Description

Calculates the conditional performance score, its sub-scores and components according to Herrmann et al. (2020) for a given simulation result from a two-stage design. Larger (sub-)score and component values refer to a better performance.

Usage

getPerformanceScore(simulationResult)

Arguments

simulationResult

A simulation result.

Author

Stephen Schueuerhuis

Details

The conditional performance score consists of two sub-scores, one for the sample size (subscoreSampleSize) and one for the conditional power (subscoreConditionalPower). Each of those are composed of a location (locationSampleSize, locationConditionalPower) and variation component (variationSampleSize, variationConditionalPower). The term conditional refers to an evaluation perspective where the interim results suggest a trial continuation with a second stage. The score can take values between 0 and 1. More details on the performance score can be found in Herrmann et al. (2020).

Examples

if (FALSE) {
# Example from Table 3 in "A new conditional performance score for 
# the evaluation of adaptive group sequential designs with samplesize 
# recalculation from Herrmann et al 2023", p.2097 for 
# Observed Conditional Power approach and Delta = 0.5

# Create two-stage Pocock design with binding futility boundary at 0
design <- getDesignGroupSequential(
    kMax = 2, typeOfDesign = "P", 
    futilityBounds = 0, bindingFutility = TRUE)

# Initialize sample sizes and effect; 
# Sample sizes are referring to overall stage-wise sample sizes
n1 <- 100
n2 <- 100
nMax <- n1 + n2
alternative <- 0.5

# Perform Simulation; nMax*1.5 defines the maximum 
# sample size for the additional stage
simulationResult <- getSimulationMeans(
    design = design,
    normalApproximation = TRUE,
    thetaH0 = 0,
    alternative = alternative,
    plannedSubjects = c(n1, nMax),
    minNumberOfSubjectsPerStage = c(NA_real_, 1),
    maxNumberOfSubjectsPerStage = c(NA_real_, nMax * 1.5),
    conditionalPower = 0.8,
    directionUpper = TRUE,
    maxNumberOfIterations = 1e05,
    seed = 140
)

# Calculate performance score
getPerformanceScore(simulationResult)
}