binom_test | R Documentation |
Performs exact binomial test and pairwise comparisons following a
significant exact multinomial test. Wrapper around the R base function
link[stats]{binom.test}()
that returns a data frame as a result.
binom_test( x, n, p = 0.5, alternative = "two.sided", conf.level = 0.95, detailed = FALSE ) pairwise_binom_test( x, p.adjust.method = "holm", alternative = "two.sided", conf.level = 0.95 ) pairwise_binom_test_against_p( x, p = rep(1/length(x), length(x)), p.adjust.method = "holm", alternative = "two.sided", conf.level = 0.95 )
x |
numeric vector containing the counts. |
n |
number of trials; ignored if |
p |
a vector of probabilities of success. The length of p must be the same as the number of groups specified by x, and its elements must be greater than 0 and less than 1. |
alternative |
indicates the alternative hypothesis and must be
one of |
conf.level |
confidence level for the returned confidence interval. |
detailed |
logical value. Default is FALSE. If TRUE, a detailed result is shown. |
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". |
return a data frame containing the p-value and its significance. with some the following columns:
group, group1, group2
:
the categories or groups being compared.
statistic
: the number
of successes.
parameter
: the number of trials.
p
:
p-value of the test.
p.adj
: the adjusted p-value.
method
: the used statistical test.
p.signif,
p.adj.signif
: the significance level of p-values and adjusted p-values,
respectively.
estimate
: the estimated probability of success.
alternative
: a character string describing the alternative
hypothesis.
conf.low,conf.high
: Lower and upper bound on a
confidence interval for the probability of success.
The returned object has an attribute called args, which is a list holding the test arguments.
binom_test()
: performs exact binomial test. Wrapper around the R
base function binom.test
that returns a dataframe as a
result.
pairwise_binom_test()
: performs pairwise comparisons (binomial test)
following a significant exact multinomial test.
pairwise_binom_test_against_p()
: performs pairwise comparisons (binomial test)
following a significant exact multinomial test for given probabilities.
multinom_test
# Exact binomial test #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # Data: 160 mice with cancer including 95 male and 65 female # Q1: Does cancer affect more males than females? binom_test(x = 95, n = 160) # => yes, there are a significant difference # Q2: compare the observed proportion of males # to an expected proportion (p = 3/5) binom_test(x = 95, n = 160, p = 3/5) # => there are no significant difference # Multinomial test #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # Data tulip <- c(red = 81, yellow = 50, white = 27) # Question 1: are the color equally common ? # this is a test of homogeneity res <- multinom_test(tulip) res attr(res, "descriptives") # Pairwise comparisons between groups pairwise_binom_test(tulip, p.adjust.method = "bonferroni") # Question 2: comparing observed to expected proportions # this is a goodness-of-fit test expected.p <- c(red = 0.5, yellow = 0.33, white = 0.17) res <- multinom_test(tulip, expected.p) res attr(res, "descriptives") # Pairwise comparisons against a given probabilities pairwise_binom_test_against_p(tulip, expected.p)
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