corAndPvalue {WGCNA} | R Documentation |
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"),
...)
Arguments
x |
a vector or a matrix |
y |
a vector or a matrix. If |
use |
determines handling of missing data. See |
alternative |
specifies the alternative hypothesis and must be (a unique abbreviation of) one of
|
... |
other arguments to the function |
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.
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. |
Author(s)
Peter Langfelder and Steve Horvath
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/
See Also
cor
for calculation of correlations only;
cor.test
for another function for significance test of correlations
Examples
# 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.