rpact (version 1.0.0)

getSampleSizeMeans: Get Sample Size Means

Description

Returns the sample size for testing means in one and two samples.

Usage

getSampleSizeMeans(design, ..., normalApproximation = FALSE,
  meanRatio = FALSE, thetaH0 = 0, alternative = seq(0.2, 1, 0.2),
  stDev = 1, groups = 2, allocationRatioPlanned = 1)

Arguments

design

The trial design.

...

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

normalApproximation

If normalApproximation = TRUE is specified, the variance is assumed to be known, default is FALSE.

meanRatio

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

thetaH0

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.

alternative

The alternative hypothesis value. This can be a vector of assumed alternatives, default is seq(0.1, 2, 0.2).

stDev

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

groups

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

allocationRatioPlanned

The planned allocation ratio for a two treatment groups design, default is 1. If allocationRatioPlanned = 0 is entered, the optimal allocation ratio yielding the smallest overall sample size is determined.

Value

Returns a TrialDesignPlanMeans object.

Details

At given design the function calculates the sample size for testing means. In a two treatment groups design, additionally, an allocation ratio = n1Fixed/n2Fixed 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.

Examples

# NOT RUN {
# Calculate sample sizes n1Fixed, n2Fixed, and 
# nFixed for a range of alternative values:
getSampleSizeMeans(getDesignGroupSequential(alpha = 0.025, sided = 1), 
    groups = 2, alternative = seq(0.1, 2, 0.2), 
    normalApproximation = FALSE, allocationRatioPlanned = 2)

# }