View source: R/compare.2.vectors.R
compare.2.vectors | R Documentation |
Compares two vectors x
and y
using t-test, Welch-test (also known as Satterthwaite), Wilcoxon-test, and a permutation test implemented in coin.
compare.2.vectors(x, y, paired = FALSE, na.rm = FALSE,
tests = c("parametric", "nonparametric"), coin = TRUE,
alternative = "two.sided",
perm.distribution,
wilcox.exact = NULL, wilcox.correct = TRUE)
x |
a (non-empty) numeric vector of data values. |
y |
a (non-empty) numeric vector of data values. |
paired |
a logical whether the data is paired. Default is |
na.rm |
logical. Should |
tests |
Which tests to report, parametric or nonparamteric? The default |
coin |
logical or character. Should (permutation) tests from the coin package be reported? Default is |
alternative |
a character, the alternative hypothesis must be one of |
perm.distribution |
|
wilcox.exact |
|
wilcox.correct |
|
The parametric
tests (currently) only contain the t-test and Welch/Statterwaithe/Smith/unequal variance t-test implemented in t.test
. The latter one is only displayed if paired = FALSE
.
The nonparametric
tests (currently) contain the Wilcoxon test implemented in wilcox.test
(stats::Wilcoxon
) and (if coin = TRUE
) the following tests implemented in coin:
a permutation
test oneway_test
(the only test in this selction not using a rank transformation),
the Wilcoxon
test wilcox_test
(coin::Wilcoxon
), and
the median
test median_test
.
Note that the two implementations of the Wilcoxon test probably differ. This is due to differences in the calculation of the Null distributions.
a list with up to two elements (i.e., paramteric
and/or nonparamteric
) each containing a data.frame
with the following columns: test
, test.statistic
, test.value
, test.df
, p
.
with(sleep, compare.2.vectors(extra[group == 1], extra[group == 2]))
# gives:
## $parametric
## test test.statistic test.value test.df p
## 1 t t -1.861 18.00 0.07919
## 2 Welch t -1.861 17.78 0.07939
##
## $nonparametric
## test test.statistic test.value test.df p
## 1 stats::Wilcoxon W 25.500 NA 0.06933
## 2 permutation Z -1.751 NA 0.08154
## 3 coin::Wilcoxon Z -1.854 NA 0.06487
## 4 median Z -1.744 NA 0.17867
# compare with:
with(sleep, compare.2.vectors(extra[group == 1], extra[group == 2],
alternative = "less"))
with(sleep, compare.2.vectors(extra[group == 1], extra[group == 2],
alternative = "greater"))
# doesn't make much sense as the data is not paired, but whatever:
with(sleep, compare.2.vectors(extra[group == 1], extra[group == 2],
paired = TRUE))
# from ?t.test:
compare.2.vectors(1:10,y=c(7:20, 200))
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