rpact: Confirmatory Adaptive Clinical Trial Design and Analysis

getPowerMeans {rpact}R Documentation

Get Power Means


Returns the power, stopping probabilities, and expected sample size for testing means in one or two samples at given sample size.


getPowerMeans(design = NULL, ..., groups = 2,
  normalApproximation = FALSE, meanRatio = FALSE,
  thetaH0 = ifelse(meanRatio, 1, 0),
  stDev = C_STDEV_DEFAULT, directionUpper = NA,
  maxNumberOfSubjects = NA_real_, allocationRatioPlanned = NA_real_)



The trial design. If no trial design is specified, a fixed sample size design is used. In this case, alpha, beta, and sided can be directly entered as argument.


Ensures that all arguments are be named and that a warning will be displayed if unknown arguments are passed.


The number of treatment groups (1 or 2), default is 2.


If normalApproximation = TRUE is specified, the variance is assumed to be known, default is FALSE, i.e., the calculations are performed with the t distribution.


If meanRatio = TRUE is specified, the power for one-sided testing of H0: mu1/mu2 = thetaH0 is calculated, default is FALSE.


The null hypothesis value. For one-sided testing, a value != 0 (or a value != 1 for testing the mean ratio) can be specified, default is 0 or 1 for difference and ratio testing, respectively.


The alternative hypothesis value. This can be a vector of assumed alternatives, default is seq(0,1,0.2).


The standard deviation, default is 1. If meanRatio = TRUE is specified, stDev defines the coefficient of variation sigma/mu2.


Specifies the direction of the alternative, only applicable for one-sided testing, default is TRUE.


maxNumberOfSubjects > 0 needs to be specified for power calculations.


The planned allocation ratio for a two treatment groups design, default is 1.


At given design the function calculates the power, stopping probabilities, and expected sample size, for testing means at given sample size. In a two treatment groups design, additionally, an allocation ratio = n1/n2 can be specified. A null hypothesis value thetaH0 != 0 for testing the difference of two means or thetaH0 != 1 for testing the ratio of two means can be specified. For the specified sample size, critical bounds and stopping for futility bounds are provided at the effect scale (mean, mean difference, or mean ratio, respectively)


Returns a TrialDesignPlanMeans object.


# Calculate the power, stopping probabilities, and expected sample size for testing H0: 
# mu1 - mu2 = 0 in a two-armed design 
# against a range of alternatives H1: mu1 - m2 = delta, delta = (0, 1, 2, 3, 4, 5), 
# standard deviation sigma = 8, maximum sample size N = 80 (both treatment arms), 
# and an allocation ratio n1/n2 = 2. The design is a three stage O'Brien & Fleming design 
# with non-binding futility bounds (-0.5, 0.5) for the two interims. 
# The computation takes into account that the t test is used (normalApproximation = FALSE). 
getPowerMeans(getDesignGroupSequential(alpha = 0.025, 
    sided = 1, futilityBounds = c(-0.5, 0.5)), 
    groups = 2, alternative = c(0:5), stDev = 8,
    normalApproximation = FALSE, maxNumberOfSubjects = 80, 
    allocationRatioPlanned = 2)

[Package rpact version 2.0.5 Index | www.rpact.org]