Rotating Rats Data

The endurance time of 24 rats in two groups in a rotating cylinder.

Usage

data(rotarod)

Format

A data frame with 24 observations on the following 2 variables.

time

the endurance time

group

a factor with levels control and treatment.

Details

The 24 rats received a fixed oral dose of a centrally acting muscle relaxant (treatment) or a saline solvent (control). They were placed on a rotating cylinder and the length of time each rat remains on the cylinder is measured, up to a maximum of 300 seconds. The rats were randomly assigned to the control and treatment group.

Note that the empirical variance in the control group is 0 and that the group medians are identical.

This dataset serves as the basis of an comparision of the results of the Wilcoxon-Mann-Whitney test computed by 11 statistical packages in Bergmann et al. (2000). The exact conditional p-value is $0.0373$ (two-sided) and $0.0186$ (one-sided). The asymptotic two-sided p-value (corrected for ties) is reported as $0.0147$.

Source

Reinhard Bergmann, John Ludbrook & Will P.J.M. Spooren (2000), Different outcomes of the Wilcoxon-Mann-Whitney test from different statistics packages. The American Statistician, 54(1), 72–77.

Examples

data(rotarod)
wilcox.exact(time ~ group, data=rotarod, alternative="g")
#> 
#> 	Exact Wilcoxon rank sum test
#> 
#> data:  time by group
#> W = 102, p-value = 0.01863
#> alternative hypothesis: true mu is greater than 0
#> 
wilcox.exact(time ~ group, data=rotarod, conf.int=TRUE)
#> 
#> 	Exact Wilcoxon rank sum test
#> 
#> data:  time by group
#> W = 102, p-value = 0.03727
#> alternative hypothesis: true mu is not equal to 0
#> 95 percent confidence interval:
#>    0 137
#> sample estimates:
#> difference in location 
#>                   14.5 
#> 
wilcox.exact(time ~ group, data=rotarod, exact=FALSE)
#> 
#> 	Asymptotic Wilcoxon rank sum test
#> 
#> data:  time by group
#> W = 102, p-value = 0.01473
#> alternative hypothesis: true mu is not equal to 0
#> 
# the permutation test
perm.test(time ~ group, data=rotarod)
#> 
#> 	2-sample Permutation Test
#> 
#> data:  time by group
#> T = 3600, p-value = 0.03727
#> alternative hypothesis: true mu is not equal to 0
#> 
perm.test(time ~ group, data=rotarod, exact=FALSE)
#> 
#> 	Asymptotic 2-sample Permutation Test
#> 
#> data:  time by group
#> T = 3600, p-value = 0.0324
#> alternative hypothesis: true mu is not equal to 0
#>