# rcorr

##### Matrix of Correlations and P-values

`rcorr`

Computes a matrix of Pearson's `r`

or Spearman's
`rho`

rank correlation coefficients for all possible pairs of
columns of a matrix. Missing values are deleted in pairs rather than
deleting all rows of `x`

having any missing variables. Ranks are
computed using efficient algorithms (see reference 2), using midranks
for ties.

- Keywords
- htest, nonparametric, category

##### Usage

`rcorr(x, y, type=c("pearson","spearman"))`# S3 method for rcorr
print(x, …)

##### Arguments

- x
a numeric matrix with at least 5 rows and at least 2 columns (if

`y`

is absent). For`print`

,`x`

is an object produced by`rcorr`

.- y
a numeric vector or matrix which will be concatenated to

`x`

. If`y`

is omitted for`rcorr`

,`x`

must be a matrix.- type
specifies the type of correlations to compute. Spearman correlations are the Pearson linear correlations computed on the ranks of non-missing elements, using midranks for ties.

- …
argument for method compatiblity.

##### Details

Uses midranks in case of ties, as described by Hollander and Wolfe.
P-values are approximated by using the `t`

or `F`

distributions.

##### Value

`rcorr`

returns a list with elements `r`

, the
matrix of correlations, `n`

the
matrix of number of observations used in analyzing each pair of variables,
and `P`

, the asymptotic P-values.
Pairs with fewer than 2 non-missing values have the r values set to NA.
The diagonals of `n`

are the number of non-NAs for the single variable
corresponding to that row and column.

##### References

Hollander M. and Wolfe D.A. (1973). Nonparametric Statistical Methods. New York: Wiley.

Press WH, Flannery BP, Teukolsky SA, Vetterling, WT (1988): Numerical Recipes in C. Cambridge: Cambridge University Press.

##### See Also

`hoeffd`

, `cor`

, `combine.levels`

,
`varclus`

, `dotchart3`

, `impute`

,
`chisq.test`

, `cut2`

.

##### Examples

```
# NOT RUN {
x <- c(-2, -1, 0, 1, 2)
y <- c(4, 1, 0, 1, 4)
z <- c(1, 2, 3, 4, NA)
v <- c(1, 2, 3, 4, 5)
rcorr(cbind(x,y,z,v))
# }
```

*Documentation reproduced from package Hmisc, version 4.3-0, License: GPL (>= 2)*

### Community examples

**catherine.crp@gmail.com**at Oct 9, 2019 Hmisc v4.2-0

```{r} #install.packages("corrplot") library(corrplot) library(Hmisc) matriz <-rcorr(as.matrix(df), type=c("spearman")) matriz ```