lpcor  R Documentation 
Estimates the linear and partial correlation coefficients using as input a data frame or a correlation matrix.
lpcor(.data, ..., by = NULL, n = NULL, method = "pearson")
.data 
The data to be analyzed. It must be a symmetric correlation
matrix or a data frame, possible with grouped data passed from

... 
Variables to use in the correlation. If 
by 
One variable (factor) to compute the function by. It is a shortcut
to 
n 
If a correlation matrix is provided, then 
method 
a character string indicating which correlation coefficient is to be computed. One of 'pearson' (default), 'kendall', or 'spearman'. 
If .data
is a grouped data passed from
dplyr::group_by()
then the results will be returned into a
listcolumn of data frames, containing:
linear.mat The matrix of linear correlation.
partial.mat The matrix of partial correlations.
results Hypothesis testing for each pairwise comparison.
Tiago Olivoto tiagoolivoto@gmail.com
library(metan) partial1 < lpcor(iris) # Alternatively using the pipe operator %>% partial2 < iris %>% lpcor() # Using a correlation matrix partial3 < cor(iris[1:4]) %>% lpcor(n = nrow(iris)) # Select all numeric variables and compute the partial correlation # For each level of Species partial4 < lpcor(iris, by = Species)
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