corAndPvalue: Calculation of correlations and associated p-values

Description

A faster, one-step calculation of Student correlation p-values for multiple correlations, properly taking into account the actual number of observations.

Usage

corAndPvalue(x, y = NULL, 
             use = "pairwise.complete.obs", 
             alternative = c("two.sided", "less", "greater"),
             ...)

Value

A list with the following components, each a matrix:

cor: the calculated correlations
p: the Student p-values corresponding to the calculated correlations
Z: Fisher transforms of the calculated correlations
t: Student t statistics of the calculated correlations
nObs: Numbers of observations for the correlation, p-values etc.

Arguments

x: a vector or a matrix
y: a vector or a matrix. If NULL, the correlation of columns of x will be calculated.
use: determines handling of missing data. See cor for details.
alternative: specifies the alternative hypothesis and must be (a unique abbreviation of) one of "two.sided", "greater" or "less". the initial letter. "greater" corresponds to positive association, "less" to negative association.
...: other arguments to the function cor.

Author

Peter Langfelder and Steve Horvath

Details

The function calculates correlations of a matrix or of two matrices and the corresponding Student p-values. The output is not as full-featured as cor.test, but can work with matrices as input.

References

Peter Langfelder, Steve Horvath (2012) Fast R Functions for Robust Correlations and Hierarchical Clustering. Journal of Statistical Software, 46(11), 1-17. https://www.jstatsoft.org/v46/i11/

Examples

Run this code

# generate random data with non-zero correlation
set.seed(1);
a = rnorm(100);
b = rnorm(100) + a;
x = cbind(a, b);
# Call the function and display all results
corAndPvalue(x)
# Set some components to NA
x[c(1:4), 1] = NA
corAndPvalue(x)
# Note that changed number of observations.

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