CT_Hypothesis_Test {ConcordanceTest} | R Documentation |
This function performs the hypothesis test for testing whether samples originate from the same distribution.
CT_Hypothesis_Test(Sample_List, Num_Sim = 10000, H = 0)
Sample_List |
List of numeric data vectors with the elements of each sample. |
Num_Sim |
The number of used simulations. The default is 10000. |
H |
0 by default. If set to 1, the Kruskal-Wallis test is also performed and returned. |
The function returns a list with the following elements:
results
: Table with the statistics and the signification levels.
C_p-value
: Concordance test signification level.
H_p-value
: Kruskal-Wallis test signification level (only if H = 1).
## Hollander & Wolfe (1973), 116. ## Mucociliary efficiency from the rate of removal of dust in normal ## subjects, subjects with obstructive airway disease, and subjects ## with asbestosis. x <- c(2.9, 3.0, 2.5, 2.6, 3.2) # normal subjects y <- c(3.8, 2.7, 4.0, 2.4) # with obstructive airway disease z <- c(2.8, 3.4, 3.7, 2.2, 2.0) # with asbestosis Sample_List <- list(x, y, z) CT_Hypothesis_Test(Sample_List, Num_Sim = 1000, H = 1) ## Example A <- c(12,13,15,20,23,28,30,32,40,48) B <- c(29,31,49,52,54) C <- c(24,26,44) Sample_List <- list(A, B, C) CT_Hypothesis_Test(Sample_List, Num_Sim = 1000, H = 1) ## Example with ties A <- c(12,13,15,20,24,29,30,32,40,49) B <- c(29,31,49,52,54) C <- c(24,26,44) Sample_List <- list(A, B, C) CT_Hypothesis_Test(Sample_List, Num_Sim = 1000, H = 1)