View source: R/normalScoresAllPairsTest.R
| normalScoresAllPairsTest | R Documentation |
Performs Lu-Smith all-pairs comparison normal scores test.
normalScoresAllPairsTest(x, ...)
## Default S3 method:
normalScoresAllPairsTest(
x,
g,
p.adjust.method = c("single-step", p.adjust.methods),
...
)
## S3 method for class 'formula'
normalScoresAllPairsTest(
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 Lu and Smith's
normal scores transformation can be used prior to
an all-pairs comparison test. A total of m = k(k-1)/2
hypotheses can be tested. The null hypothesis
H_{ij}: F_i(x) = F_j(x) is tested in the two-tailed test
against the alternative
A_{ij}: F_i(x) \ne F_j(x), ~~ i \ne j.
For p.adjust.method = "single-step" the
Tukey's studentized range distribution is used to calculate
p-values (see Tukey). Otherwise, the
t-distribution is used for the calculation of p-values
with a latter p-value adjustment as
performed by 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.
Lu, H., Smith, P. (1979) Distribution of normal scores statistic for nonparametric one-way analysis of variance. Journal of the American Statistical Association 74, 715–722.
normalScoresTest, normalScoresManyOneTest, normOrder.
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