getPowerMeans {rpact}  R Documentation 
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), alternative = C_ALTERNATIVE_POWER_SIMULATION_DEFAULT, stDev = C_STDEV_DEFAULT, directionUpper = NA, maxNumberOfSubjects = NA_real_, allocationRatioPlanned = NA_real_)
design 
The trial design. If no trial design is specified, a fixed sample size design is used.
In this case, 
... 
Ensures that all arguments are be named and that a warning will be displayed if unknown arguments are passed. 
groups 
The number of treatment groups (1 or 2), default is 
normalApproximation 
If 
meanRatio 
If 
thetaH0 
The null hypothesis value. For onesided testing, a value != 0
(or a value != 1 for testing the mean ratio) can be specified, default is 
alternative 
The alternative hypothesis value. This can be a vector of assumed
alternatives, default is 
stDev 
The standard deviation, default is 1. If 
directionUpper 
Specifies the direction of the alternative,
only applicable for onesided testing, default is 
maxNumberOfSubjects 

allocationRatioPlanned 
The planned allocation ratio for a two treatment groups
design, default is 
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 twoarmed 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 nonbinding 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)