clinfun (version 1.0.15)

power.ladesign: Power of k-sample rank test under Lehmann alternative

Description

Functions to calculate the power of rank tests for animal studies.

Usage

power.ladesign(gsize, odds.ratio, sig.level = 0.05, statistic =
     c("Kruskal-Wallis", "Jonckheere-Terpstra"), alternative =
     c("two.sided", "one.sided"), nrep=1e+6) 
  # S3 method for ladesign
print(x,…)

Arguments

gsize

sample size of the k (= length of vector) groups.

odds.ratio

odds ratio parameters for the k-1 groups. The first group is considered the control.

sig.level

the significance level of the test (default = 0.05)

statistic

the test statistic for the k-group comparison. Is one of Kruskal-Wallis (default) or Jonckeere-Terpstra.

alternative

one- or two-sided test. Valid only for the Jonckheere-Terpstra test.

nrep

number of reps (default 1 million) for Monte Carlo.

x

object of class ladesign returned by power.ladesign

...

arguments to be passed on left for S3 method consistency.

Value

returns a list with objects group.size, odds.ratio, statistic, sig.level and power. The "print" method formats the output.

Details

Although the power for Jonckheere-Terpstra test is calculated for any set of odds ratio, the test is meant for monotone alternative. Thus it is preferable to specify odds ratios that are monotonically increasing with all values larger than 1 or decreasing with all values smaller than 1.

References

Heller G. (2006). Power calculations for preclinical studies using a K-sample rank test and the Lehmann alternative hypothesis. Statistics in Medicine 25, 2543-2553.

Examples

# NOT RUN {
  power.ladesign(c(9,7), 4, statistic="K")
  power.ladesign(c(9,7,9), c(2,4), statistic="J")
  power.ladesign(c(9,7,9), c(2,4), statistic="J", alt="o")
# }