add_correlations {multitool}

Add correlations from the correlation package in easystats

Description

Add correlations from the correlation package in easystats

Usage

add_correlations(
  .df,
  var_set,
  variables,
  focus_set = NULL,
  method = "auto",
  redundant = TRUE,
  add_matrix = TRUE
)

Arguments

.df

the original data.frame(e.g., base data set). If part of set of add_* decision functions in a pipeline, the base data will be passed along as an attribute.

var_set

character string. Should be a descriptive name of the correlation matrix.

variables

the variables for which you would like to correlations. These variables will be passed to link[correlation]{correlation}. You can also use tidyselect to select variables.

focus_set

variables to focus one in a table. This produces a table where rows are each focused variables and columns are all other variables

method

a valid method of correlation supplied to link[correlation]{correlation} (e.g., 'pearson' or 'kendall'). Defaults to 'auto'. See link[correlation]{correlation} for more details.

redundant

logical, should the result include repeated correlations? Defaults to TRUE See link[correlation]{correlation} for details.

add_matrix

logical, add a traditional correlation matrix to the output. Defaults to TRUE.

Value

a data.framewith three columns: type, group, and code. Type indicates the decision type, group is a decision, and the code is the actual code that will be executed. If part of a pipe, the current set of decisions will be appended as new rows.

Examples

library(tidyverse)
library(multitool)

the_data <-
  data.frame(
    id   = 1:500,
    iv1  = rnorm(500),
    iv2  = rnorm(500),
    iv3  = rnorm(500),
    mod1 = rnorm(500),
    mod2 = rnorm(500),
    mod3 = rnorm(500),
    cov1 = rnorm(500),
    cov2 = rnorm(500),
    dv1  = rnorm(500),
    dv2  = rnorm(500),
    include1 = rbinom(500, size = 1, prob = .1),
    include2 = sample(1:3, size = 500, replace = TRUE),
    include3 = rnorm(500)
  )

the_data |>
  add_filters(include1 == 0,include2 != 3,include2 != 2, include3 > -2.5) |>
  add_variables("ivs", iv1, iv2, iv3) |>
  add_variables("dvs", dv1, dv2) |>
  add_variables("mods", starts_with("mod")) |>
  add_correlations("predictors", matches("iv|mod|cov"), focus_set = c(cov1,cov2))