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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.
rcorr.adjust(x, type = c("pearson", "spearman"),
use=c("complete.obs", "pairwise.complete.obs"))# S3 method for rcorr.adjust
print(x, ...)
a numeric matrix or data frame, or an object of class "rcorr.adjust" to be printed.
"pearson" or "spearman", depending upon the type of
correlations desired; the default is "pearson".
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.
Returns an object of class "rcorr.adjust", which is normally just printed.
# NOT RUN {
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"))
}
# }
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