WMWssp: Sample size calculation for the Wilcoxon-Mann-Whitney test.

In happma/WMWssp: Wilcoxon-Mann-Whitney Sample Size Planning

Description

This function calculates the sample size for a given power, type-I error rate and allocation rate t = n_1/N. Additionally, the actual achieved power can be simulated.

Usage

WMWssp(x, y, alpha = 0.05, power = 0.8, t = 1/2,
  simulation = FALSE, nsim = 10^4)

Arguments

x	prior information for the first group
y	prior information for the second group
alpha	two sided type I error rate
power	power
t	proportion of subjects in the first group; or use t = "min" to use optimal proportion rate
simulation	TRUE if a power simulation should be carried out
nsim	number of simulations for the power simulation

Value

Returns an object from class WMWssp containing

result	A dataframe with the results.
t	The allocation rate which was used.
alpha	The type-I error rate which was used.
simulation	The achieved power in a simulation.
power	The power which was used.
N	The sample size needed.

References

Brunner, E., Bathke A. C. and Konietschke, F. Rank- and Pseudo-Rank Procedures in Factorial Designs - Using R and SAS. Springer Verlag. to appear.

Happ, M., Bathke, A. C., & Brunner, E. (2019). Optimal Sample Size Planning for the Wilcoxon-Mann-Whitney-Test. Statistics in medicine, 38(3), 363-375.

Examples

# Prior information for the reference group
x <- c(315,375,356,374,412,418,445,403,431,410,391,475,379)
# generate data for treatment group based on a shift effect
y <- x - 20

# calculate sample size
ssp <- WMWssp(x, y, alpha = 0.05, power = 0.8, t = 1/2)
summary(ssp)

happma/WMWssp documentation built on July 9, 2019, 11:36 a.m.