cochrans.q {nonpar} | R Documentation |
Cochran's Q Test
Description
This function will perform the Cochran's Q Test to test for identical treatment effects in a two-way randomized block design with k treatments.
Usage
cochrans.q(x, alpha=NULL)
Arguments
x |
A b x k matrix, where b is the number of blocking factors and k is the number of treatment factors. |
alpha |
The Significance level, defaults to 0.05. |
Value
Q |
This is the Cochran's Q Test Statistic. |
Degrees of Freedom |
The number of degrees of freedom used in calculating the p-value. |
Significance Level |
Returns the alpha value. |
P-value |
Returns the p-value from the Cochran's Q Test. |
Author(s)
D. Lukke Sweet
References
https://www.r-bloggers.com/cochran-q-test-for-k-related-samples-in-r/
http://rcompanion.org/handbook/H_07.html
Examples
## Run Cochran's Q Test on a matrix.
cochrans.q(matrix(c(1,1,1,1,1,1,
1,1,0,1,1,1,
0,0,0,1,0,0,
0,1,0,0,1,1), 6, 4))
## Cochran's Q Test works for any size matrix.
cochrans.q(matrix(c(0,1,0,0,1,0,0,0,1,0,0,0,0,0,
0,1,1,1,1,1,1,1,0,1,1,1,1,1,
0,1,0,0,0,0,0,0,1,0,0,0,0,0,
0,1,1,0,0,1,1,0,0,0,0,1,0,1), 14, 4), alpha=0.01)
[Package nonpar version 1.0.2 Index]