This single-function package is designed to be a fast way of creating a correlation matrix from a dataframe that includes the needed variables. It also produces means, standard deviations and NHS significance tests at various levels, with an export function for the clipboard.

It is also a good tool of creating an S3 object that plugs in well into the papaja: Prepare APA Journal Articles with R Markdown package, to produce a correlation table afer the APA manuscript guidelines.

To install the latest (see latest changes below), type the following commands into the R console:

library(devtools)
devtools::install_github("GGLuca/apa.cor")

To create a correlation matrix for the Agreeableness items from the bfidataset (psych package, 25 Personality items representing 5 factors):

library(tidyverse)    # load Tidyverse
library(psych)        # load package psych for the `bfi`dataset
library(apa.cor)

bfi %>% 
  select(A1:A5) %>% 
  apa.cor()

##       M   SD      1     2     3     4
## A1 2.41 1.41                         
## A2 4.80 1.17 -.34**                  
## A3 4.60 1.30 -.27** .49**            
## A4 4.70 1.48 -.15** .34** .36**      
## A5 4.56 1.26 -.18** .39** .50** .31**

The function also has an export option export = TRUE, that copies the output into the clipboard, for further manipulation such a simple paste into Microsoft Word.

apa.cor(x, export = TRUE)

Since the function outputs a proper S3 object, it is perfect for integrating it into the papaja package, be it to create html tables or better yet, beautifully formatted PDF files.

library(papaja)

bfi %>% 
  select(A1:A5) %>% 
  apa.cor() %>% 

apa_table(
  .,
  , caption = "Variable Means, Standard Deviations, and Correlations Between Agreeableness Items"
  , note = "This table was created with apa_table()."
  , escape = TRUE
)