Skip to contents

Plot PPV Range Across Confidence Levels

Source: R/ppv_range_plots.R
plot_ppv_range.Rd

Creates a ggplot visualization showing the range of PPV estimates across the three correction methods (nominal, effective, none) as recommended by Fitzgerald et al. (2023).

Usage

plot_ppv_range(ppv_range_obj, show_band = TRUE, show_points = TRUE)

Arguments

ppv_range_obj

A lineup_ppv_range object from ppv_range_by_confidence()

show_band

Logical. Whether to show shaded uncertainty band between nominal and none estimates (default = TRUE)

show_points

Logical. Whether to show points at each confidence level (default = TRUE)

Value

A ggplot2 object

Details

The plot shows three curves:

  • Nominal (blue, dashed): Best-case estimate assuming fair lineup

  • Effective (red, solid): Size-based approximation accounting for uneven choices

  • None (gray, dashed): Worst-case estimate (no correction)

The shaded band between nominal and none represents the PPV uncertainty range due to unknown lineup fairness conditions. The effective size estimate typically falls within this range and is a size-based approximation, not a validated best estimate.

References

Fitzgerald, R. J., Tredoux, C. G., & Juncu, S. (2023). Estimation of eyewitness error rates in fair and biased lineups. Law and Human Behavior.

Examples

data(lineup_example)
ppv_range <- ppv_range_by_confidence(lineup_example,
                                     confidence_bins = c(0, 60, 80, 100))
#> Target-absent lineups contain a designated innocent suspect, so innocent-suspect IDs are counted directly and no lineup-size correction is applied. The nominal, effective and uncorrected estimates are therefore identical for these data. The three diverge only when no innocent suspect is designated and the number of innocent-suspect IDs has to be estimated from the filler IDs.
plot_ppv_range(ppv_range)