Provides a pipe-friendly framework to performs one and two sample Wilcoxon tests. Read more: Wilcoxon in R.

```
wilcox_test(
data,
formula,
comparisons = NULL,
ref.group = NULL,
p.adjust.method = "holm",
paired = FALSE,
exact = NULL,
alternative = "two.sided",
mu = 0,
conf.level = 0.95,
detailed = FALSE
)
pairwise_wilcox_test(
data,
formula,
comparisons = NULL,
ref.group = NULL,
p.adjust.method = "holm",
detailed = FALSE,
...
)
```

- data
a data.frame containing the variables in the formula.

- formula
a formula of the form

`x ~ group`

where`x`

is a numeric variable giving the data values and`group`

is a factor with one or multiple levels giving the corresponding groups. For example,`formula = TP53 ~ cancer_group`

.- comparisons
A list of length-2 vectors specifying the groups of interest to be compared. For example to compare groups "A" vs "B" and "B" vs "C", the argument is as follow:

`comparisons = list(c("A", "B"), c("B", "C"))`

- ref.group
a character string specifying the reference group. If specified, for a given grouping variable, each of the group levels will be compared to the reference group (i.e. control group).

If

`ref.group = "all"`

, pairwise two sample tests are performed for comparing each grouping variable levels against all (i.e. basemean).- p.adjust.method
method to adjust p values for multiple comparisons. Used when pairwise comparisons are performed. Allowed values include "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none". If you don't want to adjust the p value (not recommended), use p.adjust.method = "none".

- paired
a logical indicating whether you want a paired test.

- exact
a logical indicating whether an exact p-value should be computed.

- alternative
a character string specifying the alternative hypothesis, must be one of

`"two.sided"`

(default),`"greater"`

or`"less"`

. You can specify just the initial letter.- mu
a number specifying an optional parameter used to form the null hypothesis.

- conf.level
confidence level of the interval.

- detailed
logical value. Default is FALSE. If TRUE, a detailed result is shown.

- ...
other arguments to be passed to the function

`wilcox.test`

.

return a data frame with some of the following columns:

`.y.`

: the y variable used in the test.`group1,group2`

: the compared groups in the pairwise tests.`n,n1,n2`

: Sample counts.`statistic`

: Test statistic used to compute the p-value.`p`

: p-value.`p.adj`

: the adjusted p-value.`method`

: the statistical test used to compare groups.`p.signif, p.adj.signif`

: the significance level of p-values and adjusted p-values, respectively.`estimate`

: an estimate of the location parameter (Only present if argument`detailed = TRUE`

). This corresponds to the pseudomedian (for one-sample case) or to the difference of the location parameter (for two-samples case).The pseudomedian of a distribution

`F`

is the median of the distribution of`(u+v)/2`

, where`u`

and v are independent, each with distribution`F`

. If`F`

is symmetric, then the pseudomedian and median coincide.Note that in the two-sample case the estimator for the difference in location parameters does not estimate the difference in medians (a common misconception) but rather the median of the difference between a sample from x and a sample from y.

`conf.low, conf.high`

: a confidence interval for the location parameter. (Only present if argument conf.int = TRUE.)

The **returned object has an attribute called args**, which is a list
holding the test arguments.

- `pairwise_wilcox_test()`

applies the standard two sample
Wilcoxon test to all possible pairs of groups. This method calls the
`wilcox.test()`

, so extra arguments are accepted.

- If a list of comparisons is specified, the result of the pairwise tests is filtered to keep only the comparisons of interest.The p-value is adjusted after filtering.

- For a grouped data, if pairwise test is performed, then the p-values are adjusted for each group level independently.

- a nonparametric confidence interval and an estimator for the pseudomedian
(one-sample case) or for the difference of the location parameters
`x-y`

is computed, where x and y are the compared samples or groups.
The column `estimate`

and the confidence intervals are displayed in the
test result when the option `detailed = TRUE`

is specified in the
`wilcox_test()`

and `pairwise_wilcox_test()`

functions. Read more
about the calculation of the estimate in the details section of the R base
function `wilcox.test()`

documentation by typing `?wilcox.test`

in
the R console.

`wilcox_test()`

: Wilcoxon test`pairwise_wilcox_test()`

: performs pairwise two sample Wilcoxon test.

```
# Load data
#:::::::::::::::::::::::::::::::::::::::
data("ToothGrowth")
df <- ToothGrowth
# One-sample test
#:::::::::::::::::::::::::::::::::::::::::
df %>% wilcox_test(len ~ 1, mu = 0)
#> Error in UseMethod("wilcox_test"): no applicable method for 'wilcox_test' applied to an object of class "data.frame"
# Two-samples unpaired test
#:::::::::::::::::::::::::::::::::::::::::
df %>% wilcox_test(len ~ supp)
#> Error in UseMethod("wilcox_test"): no applicable method for 'wilcox_test' applied to an object of class "data.frame"
# Two-samples paired test
#:::::::::::::::::::::::::::::::::::::::::
df %>% wilcox_test (len ~ supp, paired = TRUE)
#> Error in UseMethod("wilcox_test"): no applicable method for 'wilcox_test' applied to an object of class "data.frame"
# Compare supp levels after grouping the data by "dose"
#::::::::::::::::::::::::::::::::::::::::
df %>%
group_by(dose) %>%
wilcox_test(data =., len ~ supp) %>%
adjust_pvalue(method = "bonferroni") %>%
add_significance("p.adj")
#> Error in add_significance(., "p.adj"): The column p.adj does not exist in the data
# pairwise comparisons
#::::::::::::::::::::::::::::::::::::::::
# As dose contains more than two levels ==>
# pairwise test is automatically performed.
df %>% wilcox_test(len ~ dose)
#> Error in UseMethod("wilcox_test"): no applicable method for 'wilcox_test' applied to an object of class "data.frame"
# Comparison against reference group
#::::::::::::::::::::::::::::::::::::::::
# each level is compared to the ref group
df %>% wilcox_test(len ~ dose, ref.group = "0.5")
#> Error in UseMethod("wilcox_test"): no applicable method for 'wilcox_test' applied to an object of class "data.frame"
# Comparison against all
#::::::::::::::::::::::::::::::::::::::::
df %>% wilcox_test(len ~ dose, ref.group = "all")
#> Error in UseMethod("wilcox_test"): no applicable method for 'wilcox_test' applied to an object of class "data.frame"
```