Add a set of variable alternatives to a multiverse pipeline

Usage

add_variables(.df, var_group, ...)

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_group: a character string. Indicates the name of the current set. For example, "primary_iv" could indicate this set are alternatives of the main predictor in an analysis.
...: the bare unquoted names of the variables to include as alternative options for this variable set. You can also use tidyselect to select variables.

Value

a data.frame with 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)

# Simulate some data
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_variables("ivs", iv1, iv2, iv3) |>
 add_variables("dvs", dv1, dv2) |>
 add_variables("mods", starts_with("mod"))
#> # A tibble: 8 × 3
#>   type      group code 
#>   <chr>     <chr> <chr>
#> 1 variables ivs   iv1  
#> 2 variables ivs   iv2  
#> 3 variables ivs   iv3  
#> 4 variables dvs   dv1  
#> 5 variables dvs   dv2  
#> 6 variables mods  mod1 
#> 7 variables mods  mod2 
#> 8 variables mods  mod3