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Performs Nemenyi's non-parametric many-to-one comparison test for Friedman-type ranked data.
frdManyOneNemenyiTest(y, ...)# S3 method for default
frdManyOneNemenyiTest(y, groups, blocks,
alternative = c("two.sided", "greater", "less"), ...)
a numeric vector of data values, or a list of numeric data vectors.
a vector or factor object giving the group for the
corresponding elements of "x"
. Ignored with a warning if "x"
is a list.
a vector or factor object giving the block for the
corresponding elements of "x"
.
Ignored with a warning if "x"
is a list.
the alternative hypothesis. Defaults to two.sided
.
further arguments to be passed to or from methods.
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 many-to-one comparisons (pairwise comparisons with one control) in a two factorial unreplicated complete block design with non-normally distributed residuals, Nemenyi's test can be performed on Friedman-type ranked data.
Let there be
The
Hollander, M., Wolfe, D. A., Chicken, E. (2014), Nonparametric Statistical Methods. 3rd ed. New York: Wiley. 2014.
Miller Jr., R. G. (1996), Simultaneous Statistical Inference. New York: McGraw-Hill.
Nemenyi, P. (1963), Distribution-free Multiple Comparisons. Ph.D. thesis, Princeton University.
Siegel, S., Castellan Jr., N. J. (1988), Nonparametric Statistics for the Behavioral Sciences. 2nd ed. New York: McGraw-Hill.
Zarr, J. H. (1999), Biostatistical Analysis. 4th ed. Upper Saddle River: Prentice-Hall.
friedmanTest
, friedman.test
,
frdManyOneExactTest
, frdManyOneDemsarTest
pmvnorm
# NOT RUN {
## Sachs, 1997, p. 675
## Six persons (block) received six different diuretics
## (A to F, treatment).
## The responses are the Na-concentration (mval)
## in the urine measured 2 hours after each treatment.
## Assume A is the control.
y <- matrix(c(
3.88, 5.64, 5.76, 4.25, 5.91, 4.33, 30.58, 30.14, 16.92,
23.19, 26.74, 10.91, 25.24, 33.52, 25.45, 18.85, 20.45,
26.67, 4.44, 7.94, 4.04, 4.4, 4.23, 4.36, 29.41, 30.72,
32.92, 28.23, 23.35, 12, 38.87, 33.12, 39.15, 28.06, 38.23,
26.65),nrow=6, ncol=6,
dimnames=list(1:6, LETTERS[1:6]))
## Global Friedman test
friedmanTest(y)
## Demsar's many-one test
frdManyOneDemsarTest(y=y, p.adjust = "bonferroni")
## Exact many-one test
frdManyOneExactTest(y=y, p.adjust = "bonferroni")
## Nemenyi's many-one test
frdManyOneNemenyiTest(y=y)
# }
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