Build the experimental conditions — design

Start with the factors you want to vary. This function crosses their levels into a design with one row per condition. Each column becomes a {placeholder} in the prompt passed to generate_materials.

Usage

design_conditions(..., .exclude = NULL)

Arguments

...: Named character or factor vectors, one per experimental factor. For example frame = c("economic", "moral"), source = c("expert", "layperson").
.exclude: Optional function taking the design tibble and returning a logical vector. Rows where it returns TRUE are dropped, which is useful for removing impossible or off-limits factor combinations.

Value

A tibble with one row per condition, a condition_id column, and one column per factor.

Details

I'd use .exclude to remove combinations that wouldn't make sense in the study before asking a model to write them.

Examples

design_conditions(
  frame  = c("economic", "moral"),
  source = c("expert", "layperson")
)
#> ℹ Design: 4 conditions from 2 factors
#> # A tibble: 4 × 3
#>   condition_id frame    source   
#>          <int> <chr>    <chr>    
#> 1            1 economic expert   
#> 2            2 moral    expert   
#> 3            3 economic layperson
#> 4            4 moral    layperson

# Drop an implausible cell
design_conditions(
  frame  = c("economic", "moral"),
  source = c("expert", "layperson"),
  .exclude = function(d) d$frame == "moral" & d$source == "expert"
)
#> ℹ Design: 3 conditions from 2 factors
#> # A tibble: 3 × 3
#>   condition_id frame    source   
#>          <int> <chr>    <chr>    
#> 1            1 economic expert   
#> 2            2 economic layperson
#> 3            3 moral    layperson