RcmdrMisc (version 2.9-1)

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

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.

Usage

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

Value

Returns an object of class "rcorr.adjust", which is normally just printed.

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.

Author

John Fox, adapting code from Robert A. Muenchen.

See Also

rcorr, p.adjust.

Examples

if (require(car)){
    data(Mroz)
    print(rcorr.adjust(Mroz[,c("k5", "k618", "age", "lwg", "inc")]))
    print(rcorr.adjust(Mroz[,c("k5", "k618", "age", "lwg", "inc")], type="spearman"))
    }