test_between_factors {cola}R Documentation

Test whether a list of factors are correlated

Description

Test whether a list of factors are correlated

Usage

test_between_factors(x, y = NULL, all_factors = FALSE, verbose = FALSE)

Arguments

x

a data frame or a vector which contains discrete or continuous variables. if y is omit, pairwise testing for columns in x is performed.

y

a data frame or a vector which contains discrete or continuous variables.

all_factors

are all columns in x and y are enforced to be factors?

verbose

whether to print messages.

Details

Pairwise test is applied to every two columns in the data frames. Methods are:

This function can be used to test the correlation between the predicted classes and other known factors.

Value

A matrix of p-values. If there are NA values, basically it means there are no efficient data points to perform the test.

Author(s)

Zuguang Gu <z.gu@dkfz.de>

Examples

df = data.frame(v1 = rnorm(100), v2 = sample(letters[1:3], 100, replace = TRUE), 
    v3 = sample(LETTERS[5:6], 100, replace = TRUE))
test_between_factors(df)
x = runif(100)
test_between_factors(x, df)

[Package cola version 1.0.0 Index]