Conover's All-Pairs Rank Comparison Test
Performs Conover's non-parametric all-pairs comparison test for Kruskal-type ranked data.
kwAllPairsConoverTest(x, ...)
## Default S3 method:
kwAllPairsConoverTest(
x,
g,
p.adjust.method = c("single-step", p.adjust.methods),
...
)
## S3 method for class 'formula'
kwAllPairsConoverTest(
formula,
data,
subset,
na.action,
p.adjust.method = c("single-step", p.adjust.methods),
...
)x |
a numeric vector of data values, or a list of numeric data vectors. |
... |
further arguments to be passed to or from methods. |
g |
a vector or factor object giving the group for the
corresponding elements of |
p.adjust.method |
method for adjusting p values
(see |
formula |
a formula of the form |
data |
an optional matrix or data frame (or similar: see
|
subset |
an optional vector specifying a subset of observations to be used. |
na.action |
a function which indicates what should happen when
the data contain |
For all-pairs comparisons in an one-factorial layout with non-normally distributed residuals Conover's non-parametric test can be performed. A total of m = k(k-1)/2 hypotheses can be tested. The null hypothesis H_{ij}: μ_i(x) = μ_j(x) is tested in the two-tailed test against the alternative A_{ij}: μ_i(x) \ne μ_j(x), ~~ i \ne j.
If p.adjust.method == "single-step" the p-values are computed
from the studentized range distribution. Otherwise,
the p-values are computed from the t-distribution using
any of the p-adjustment methods as included in p.adjust.
A list with class "PMCMR" containing the following components:
a character string indicating what type of test was performed.
a character string giving the name(s) of the data.
lower-triangle matrix of the estimated quantiles of the pairwise test statistics.
lower-triangle matrix of the p-values for the pairwise tests.
a character string describing the alternative hypothesis.
a character string describing the method for p-value adjustment.
a data frame of the input data.
a string that denotes the test distribution.
Conover, W. J, Iman, R. L. (1979) On multiple-comparisons procedures, Tech. Rep. LA-7677-MS, Los Alamos Scientific Laboratory.
## Data set InsectSprays
## Global test
kruskalTest(count ~ spray, data = InsectSprays)
## Conover's all-pairs comparison test
## single-step means Tukey's p-adjustment
ans <- kwAllPairsConoverTest(count ~ spray, data = InsectSprays,
p.adjust.method = "single-step")
summary(ans)
## Dunn's all-pairs comparison test
ans <- kwAllPairsDunnTest(count ~ spray, data = InsectSprays,
p.adjust.method = "bonferroni")
summary(ans)
## Nemenyi's all-pairs comparison test
ans <- kwAllPairsNemenyiTest(count ~ spray, data = InsectSprays)
summary(ans)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.