sign_test | R Documentation |
Performs one-sample and two-sample sign tests. Read more: Sign Test in R.
sign_test( data, formula, comparisons = NULL, ref.group = NULL, p.adjust.method = "holm", alternative = "two.sided", mu = 0, conf.level = 0.95, detailed = FALSE ) pairwise_sign_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 |
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: |
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). |
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". |
alternative |
a character string specifying the alternative
hypothesis, must be one of |
mu |
a single number representing the value of the population median specified by 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 passed to the function |
return a data frame with some 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. That is
the S-statistic (the number of positive differences between the data and the
hypothesized median), with names attribute "S"
.
df,
parameter
: degrees of freedom. Here, the total number of valid differences.
p
: 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
:
estimate of the effect size. It corresponds to the median of the
differences.
alternative
: a character string describing the
alternative hypothesis.
conf.low,conf.high
: Lower and upper
bound on a confidence interval of the estimate.
The returned object has an attribute called args, which is a list holding the test arguments.
sign_test()
: Sign test
pairwise_sign_test()
: performs pairwise two sample Wilcoxon test.
This function is a reimplementation of the function SignTest()
from the DescTools
package.
# Load data #::::::::::::::::::::::::::::::::::::::: data("ToothGrowth") df <- ToothGrowth # One-sample test #::::::::::::::::::::::::::::::::::::::::: df %>% sign_test(len ~ 1, mu = 0) # Two-samples paired test #::::::::::::::::::::::::::::::::::::::::: df %>% sign_test(len ~ supp) # Compare supp levels after grouping the data by "dose" #:::::::::::::::::::::::::::::::::::::::: df %>% group_by(dose) %>% sign_test(data =., len ~ supp) %>% adjust_pvalue(method = "bonferroni") %>% add_significance("p.adj") # pairwise comparisons #:::::::::::::::::::::::::::::::::::::::: # As dose contains more than two levels ==> # pairwise test is automatically performed. df %>% sign_test(len ~ dose) # Comparison against reference group #:::::::::::::::::::::::::::::::::::::::: # each level is compared to the ref group df %>% sign_test(len ~ dose, ref.group = "0.5")
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