kepner_robinson_test_internal: Kepner-Robinson Test

In happma/pseudorank: Pseudo-Ranks

Kepner-Robinson Test

Description

This function calculates the Kepner-Robinsin test under the null hypothesis H0F: F_1 = ... F_k.

Usage

kepner_robinson_test_internal(
  data,
  time,
  subject,
  distribution,
  na.rm,
  formula = NULL,
  ...
)

Arguments

data	numeric vector containing the data
time	factor vector containing time points
subject	factor vector containing subjects
distribution	specified distribution, either Chisq or F
na.rm	a logical value indicating if NA values should be removed
formula	formula object
...	further arguments are ignored

Value

Returns a data.frame with the results

References

Kepner, J. L., & Robinson, D. H. (1988). Nonparametric methods for detecting treatment effects in repeated-measures designs. Journal of the American Statistical Association, 83(402), 456-461.

Examples

# create some artificial data with 20 subjects measured at two time points
data <- rnorm(40)
time <- rep(c(1,2),20)
subject <- gl(20,2)
df <- data.frame(data=data,time=time,subject=subject)

kepner_robinson_test(data,time,subject)
kepner_robinson_test(data~time,data=df,subject="subject")

happma/pseudorank documentation built on Feb. 22, 2025, 1:46 p.m.