Compute and Plot RAC for Lineup Identification

Main function to compute and plot RAC (Response Time-Accuracy Characteristic) for eyewitness lineup data.

Usage

make_rac(
  data,
  lineup_size = 6,
  time_bins = NULL,
  show_plot = TRUE,
  innocent_suspect = "auto",
  ...
)

Arguments

data

A dataframe with columns: target_present, identification, response_time

lineup_size

Integer. Number of people in lineup (default = 6)

time_bins

Numeric vector of bin edges (recommended for continuous RT data)

show_plot

Logical. Whether to display the plot (default = TRUE)

innocent_suspect

How innocent-suspect identifications in target-absent lineups are obtained. "designated": the lineups had a designated innocent suspect, so target-absent "suspect" rows are counted directly, and zero such rows means a false-ID rate of zero. "estimated": there was no designated innocent suspect, so the innocent-suspect count is estimated as filler IDs divided by lineup_size. "auto" (the default) chooses "designated" when any target-absent row is a suspect ID or the data have a non-missing suspect_pos column, and "estimated" otherwise, with a message.

...

Additional arguments passed to make_rac_gg()

Value

A list containing RAC data and plot

Examples

# Example with binned response times (in milliseconds)
lineup_data <- create_example_lineup_data(n_trials = 200,
                                          include_response_time = TRUE,
                                          seed = 123)
rac_result <- make_rac(lineup_data,
                       time_bins = c(0, 5000, 10000, 15000, 20000))
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_line()`).
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_text()`).

print(rac_result)
#> 
#> === Lineup RAC Analysis ===
#> 
#> Overall Accuracy: 0.838 
#> Total Suspect IDs: 74 
#> Lineup size: 6 
#> 
#> RAC Data:
#> # A tibble: 4 × 7
#>   response_time mean_time n_correct n_incorrect n_total accuracy      se
#>   <chr>             <dbl>     <int>       <int>   <int>    <dbl>   <dbl>
#> 1 [0,5000]          3337.        33           8      41    0.805  0.0619
#> 2 (5000,10000]      6657.        29           4      33    0.879  0.0568
#> 3 (10000,15000]       NA          0           0       0   NA     NA     
#> 4 (15000,20000]       NA          0           0       0   NA     NA     
#> 
#> Plot: save this object first, then extract it with x$plot
rac_result$plot
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_line()`).
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_text()`).