Description Usage Arguments Value References Examples
View source: R/kepner_robinson.R
This function calculates the Kepner-Robinsin test under the null hypothesis H0F: F_1 = ... F_k.
1 2 3 4 5 6 7 8 9 | kepner_robinson_test_internal(
data,
time,
subject,
distribution,
na.rm,
formula = NULL,
...
)
|
data |
numeric vector containing the data |
na.rm |
a logical value indicating if NA values should be removed |
formula |
formula object |
... |
further arguments are ignored |
group |
ordered factor vector for the groups |
alternative |
either decreasing or increasing |
trend |
custom numeric vector indicating the trend for the custom alternative, only used if alternative = "custom" |
Returns a data.frame with the results
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.
1 2 3 4 5 |
Kruskal-Wallis Test
Test Statistic: 6.736842
Distribution of Statistic: Chisq
Degrees of Freedom: 2
unweighted relative Effects / Pseudo-ranks: TRUE
p-Value: 0.03444398
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