# rcorr.adjust

From Rcmdr v2.0-4
by John Fox

##### Compute Pearson or Spearman Correlations with p-Values

This function uses the `rcorr`

function in the `p.adjust`

).
Observations are filtered for missing data, and only complete observations are used.
The `partial.cor`

function may similarly be used to get p-values and
adjusted p-values for partial correlations.

- Keywords
- htest

##### Usage

```
rcorr.adjust(x, type = c("pearson", "spearman"),
use=c("complete.obs", "pairwise.complete.obs"))
## S3 method for class 'rcorr.adjust':
print(x, ...)
```

##### Arguments

- x
- a numeric matrix or data frame, or an object of class
`"rcorr.adjust"`

to be printed. - type
`"pearson"`

or`"spearman"`

, depending upon the type of correlations desired; the default is`"pearson"`

.- use
- how to handle missing data:
`"complete.obs"`

, the default, use only complete cases;`"pairwise.complete.obs"`

, use all cases with valid data for each pair. - ...
- not used.

##### Value

- Returns an object of class
`"rcorr.adjust"`

, which is normally just printed.

##### See Also

##### Examples

```
data(Mroz, package="car")
rcorr.adjust(Mroz[,c("k5", "k618", "age", "lwg", "inc")])
rcorr.adjust(Mroz[,c("k5", "k618", "age", "lwg", "inc")], type="spearman")
```

*Documentation reproduced from package Rcmdr, version 2.0-4, License: GPL (>= 2)*

### Community examples

Looks like there are no examples yet.