Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
# S3 method for rcorr tidy(x, diagonal = FALSE, ...)
x | An |
---|---|
diagonal | Logical indicating whether or not to include diagonal
elements of the correlation matrix, or the correlation of a column with
itself. For the elements, |
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
Suppose the original data has columns A and B. In the correlation
matrix from rcorr
there may be entries for both the cor(A, B)
and
cor(B, A)
. Only one of these pairs will ever be present in the tidy
output.
A tibble::tibble()
with columns:
Name or index of the first column being described.
Name or index of the second column being described.
The estimated value of the regression term.
The two-sided p-value associated with the observed statistic.
Number of observations used to compute the correlation
if (requireNamespace("Hmisc", quietly = TRUE)) { library(Hmisc) mat <- replicate(52, rnorm(100)) # add some NAs mat[sample(length(mat), 2000)] <- NA # also column names colnames(mat) <- c(LETTERS, letters) rc <- rcorr(mat) td <- tidy(rc) td library(ggplot2) ggplot(td, aes(p.value)) + geom_histogram(binwidth = .1) ggplot(td, aes(estimate, p.value)) + geom_point() + scale_y_log10() } #> Loading required package: Formula #> #> Attaching package: ‘Hmisc’ #> The following object is masked from ‘package:psych’: #> #> describe #> The following object is masked from ‘package:network’: #> #> is.discrete #> The following object is masked from ‘package:survey’: #> #> deff #> The following objects are masked from ‘package:dplyr’: #> #> src, summarize #> The following objects are masked from ‘package:base’: #> #> format.pval, units