rcorr.adjust: Compute Pearson or Spearman Correlations with p-Values

In Rcmdr205: R Commander

Description

This function uses the rcorr function in the Hmisc package to compute matrices of Pearson or Spearman correlations along with the pairwise p-values among the correlations. The p-values are corrected for multiple inference using Holm's method (see 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.

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.

Author(s)

John Fox, adapting code from Robert A. Muenchen.

See Also

rcorr, p.adjust, partial.cor.

Examples

	## Not run: 
data(Mroz, package="car")
rcorr.adjust(Mroz[,c("k5", "k618", "age", "lwg", "inc")])
rcorr.adjust(Mroz[,c("k5", "k618", "age", "lwg", "inc")], type="spearman")
	
## End(Not run)

Rcmdr205 documentation built on May 2, 2019, 5:52 p.m.