View source: R/statistical_tests_and_estimates.R
two_samp_bin_test | R Documentation |
Either Barnard, Fisher's, or Chi-sq test performed for unpaired data and McNemar's test for paired data
two_samp_bin_test(
x,
y,
method = c("barnard", "fisher", "chi.sq", "mcnemar"),
barnard_method = c("z-pooled", "z-unpooled", "boschloo", "santner and snell", "csm",
"csm approximate", "csm modified"),
alternative = c("two.sided", "less", "greater"),
verbose = FALSE,
...
)
x |
vector with only 2 levels (can include NA values). |
y |
vector with only 2 levels (can include NA values unless
|
method |
what test to run, "barnard" (default), "fisher" , "chi.sq" , or "mcnemar") |
barnard_method |
indicates the Barnard method for finding tables as or
more extreme than the observed table: must be either "z-pooled",
"z-unpooled", "santner and snell", "boschloo", "csm", "csm approximate", or
"csm modified". Only used when |
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. Only "two.sided" available for
|
verbose |
a logical variable indicating if warnings and messages should be displayed. |
... |
other parameters to pass to Exact::exact.test when running Barnard test |
For one sided tests if y
is a factor variable the level order is
respected, otherwise the levels will set to alphabetical order (i.e. if
alternative = less
then testing a < b ).
If method = 'mcnemar'
assumes the first observations of the first
group matches the first observation of the second group, and so on. Also if
method = 'mcnemar'
then y
must have the same number of samples
for each level.
If only one value of x
than p=1
is returned, however if only one value of y
than p=NA
is returned. This is to match expactations since normally y is a group variable
and x is the outcome (i.e. if both group response rates are 0\
returned)
p-value for comparing x at the different levels of y.
set.seed(5432322)
outcome <- c(sample(0:1,10,replace = TRUE, prob = c(.75,.25)),
sample(0:1,10,replace = TRUE, prob = c(.25,.75)))
grp <- c(rep('a', 10), rep('b', 10))
two_samp_bin_test(outcome, grp, method = 'barnard')
two_samp_bin_test(outcome, grp, 'fisher')
two_samp_bin_test(outcome, grp, 'chi.sq')
two_samp_bin_test(outcome, grp, 'mcnemar')
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