Description Usage Arguments Value Note
PIM implementations of distributionfree tests
1 2 3 4 | classical.test(test = c("WilcoxonMannWhitney", "KruskalWallis",
"MackSkillings", "BrownHettmansperger", "JonckheereTerpstra", "MackWolfe"),
data, out, group, block, varianceestimator = varianceestimator.H0(),
alternative = c("two.sided", "greater", "less"), levelP, verbosity = 0)
|
test |
Type of "classical" distribution free test to perform. |
data |
Context where |
out |
Column of |
group |
Column of |
block |
Column of |
varianceestimator |
Function like the result of |
alternative |
As for other tests |
levelP |
The level of the grouping variable that is the "top" of the umbrella (only
relevant for |
verbosity |
The higher this value, the more levels of progress and debug information is displayed (note: in R for Windows, turn off buffered output) |
a list holding the following items:
statistic |
The test statistic. |
p.value |
p-value for the test. |
df |
Degress of freedom (if relevant, otherwise |
conversion |
Function to convert the pim estimates to the test statistic. |
These functions are merely provided for comparison. The pim function supports
generic ways of estimating these values. For generosity, the parameters to all of
them are the same, though some are not relevant (e.g. block
for WMW).
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