Continuous Variable Compared to Binary Variable Test

Either Wilcox or T-Test Performed, for unpaired or paired data

two_samp_cont_test(x, y, method = c("wilcox", "t.test"),
  paired = FALSE, verbose = FALSE, ...)

Arguments

x	numeric vector (can include NA values).
y	vector with only 2 levels (can include NA values unless paired = TRUE).
method	what test to run (wilcox or t-test).
paired	a logical indicating whether you want a paired test.
verbose	a logical variable indicating if warnings and messages should be displayed.
...	parameters to pass to wilcox_test or t.test functions. For example the testing direction (alternative) in either call or the var.equal in the t.test function.

Value

p-value for comparing x at the different levels of y.

Details

Runs wilcox_test() in the coin package, with "exact" distribution and mid-ranks ties method.

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 paired = TRUE assumes the first observations of the first group matches the first observation of the second group, and so on. Also if paired = TRUE then y must have the same number of samples for each level.

Examples

set.seed(5432322)
x <- c(rnorm(10,0,3), rnorm(10,3,3))
y <- c(rep('a', 10), rep('b', 10))
two_samp_cont_test(x = x, y = y, method = 'wilcox', paired = FALSE)
#> [1] 0.01854338
two_samp_cont_test(x = x, y = y, method = 'wilcox', paired = TRUE)
#> [1] 0.06445312
two_samp_cont_test(x = x, y = y, method = 't', paired = FALSE)
#> [1] 0.01890551
two_samp_cont_test(x = x, y = y, method = 't', paired = TRUE)
#> [1] 0.03394079