Performs Lu-Smith all-pairs comparison normal scores test.
normalScoresAllPairsTest(x, ...)# S3 method for default
normalScoresAllPairsTest(
x,
g,
p.adjust.method = c("single-step", p.adjust.methods),
...
)
# S3 method for formula
normalScoresAllPairsTest(
formula,
data,
subset,
na.action,
p.adjust.method = c("single-step", p.adjust.methods),
...
)
a numeric vector of data values, or a list of numeric data vectors.
further arguments to be passed to or from methods.
a vector or factor object giving the group for the
corresponding elements of "x"
.
Ignored with a warning if "x"
is a list.
method for adjusting p values (see p.adjust
).
a formula of the form response ~ group
where
response
gives the data values and group
a vector or
factor of the corresponding groups.
an optional matrix or data frame (or similar: see
model.frame
) containing the variables in the
formula formula
. By default the variables are taken from
environment(formula)
.
an optional vector specifying a subset of observations to be used.
a function which indicates what should happen when
the data contain NA
s. Defaults to getOption("na.action")
.
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.
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
.
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.