compare.2.vectors {afex}  R Documentation 
Compares two vectors x
and y
using ttest, Welchtest (also known as Satterthwaite), Wilcoxontest, 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 (nonempty) numeric vector of data values. 
y 
a (nonempty) 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 ttest and Welch/Statterwaithe/Smith/unequal variance ttest 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))