mm.test | R Documentation |
mm.test()
performs all possible mean comparison tests, even if not mathematically correct and even if hypotheses are wrong. It executes tests to verify hypotheses, and the results are summarized in a graph. The user needs to choose the correct path, which can be done automatically by m.test()
. By default, it finds the path that is more to the left.
mm.test(
x,
group,
pval = 0.05,
verbose = FALSE,
return = TRUE,
paired = FALSE,
pval_ks = 0.01,
maxcat = 50,
plot = TRUE,
silent = TRUE,
boot = FALSE,
iter = 100,
conf = 0.95,
code = FALSE,
debug. = FALSE
)
x |
The values: a vector of values, with the samples to be compared. |
group |
Categories: a vector of factors with fewer than maxcat categories. |
pval |
The usual confidence level, 0.05 by default. |
verbose |
|
return |
Logical. Should the results be returned? Default is |
paired |
|
pval_ks |
The p-value for distribution tests like Kolmogorov-Smirnov or Shapiro: 0.01 by default. |
maxcat |
The maximum number of categories: 50 by default. |
plot |
|
silent |
|
boot |
|
iter |
Number of iterations in the bootstrap, 100 by default. |
conf |
Confidence level of the bootstrap, 0.95 by default. |
code |
If |
debug. |
|
A list containing the results of the tests.
Julien BOUSQUET (2021)
# Example 1
data(iris)
#mm.test(iris$Sepal.Length, iris$Species)
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