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Classify Raw Lineup Choices into Identification Outcomes

Source: R/classify_choices.R
classify_lineup_choices.Rd

Derives an identification outcome — suspect identification, foil identification, or rejection — from the raw record of which lineup member each witness actually chose.

Usage

classify_lineup_choices(
  data,
  member_col = "lineup_member",
  suspect_col = "suspect_pos",
  into = "identification",
  k = NULL,
  overwrite = FALSE
)

Arguments

data

A data frame of lineup trials, one row per witness.

member_col

Name of the column holding the position of the lineup member chosen, with 0 (or NA) denoting a rejection. Defaults to "lineup_member".

suspect_col

Either the name of a column holding the suspect's position for each trial, or a single number giving a suspect position common to all trials. Defaults to "suspect_pos".

into

Name of the column to write the derived outcome into. Defaults to "identification".

k

Optional lineup size. When supplied, choices are checked to lie in 0:k and the positions of any null foils are attached to the result as the "null_foils" attribute.

overwrite

Logical. Whether to overwrite into if it already exists. Defaults to FALSE, which raises an error instead.

Value

data with the derived outcome column added. If k was supplied, the "null_foils" attribute gives the positions that no witness chose.

Details

Lineup data should record which member a witness chose, not merely whether the choice happened to fall on the suspect. Foils are not interchangeable: they differ in how plausible they are, and a foil that no witness ever chooses is not a functioning alternative to the suspect. Storing only a collapsed "suspect / filler / reject" label discards the information needed to see that.

This function treats the collapsed label as derived. Raw data keeps the chosen position; classify_lineup_choices() produces the label on demand, so both are available and the two cannot drift apart.

The outcome is "suspect" when the chosen member is the suspect, "reject" when no member was chosen, and "filler" otherwise. These are the labels used throughout the package, so the result can be passed straight to make_roc, make_cac and the other analysis functions.

References

Malpass, R. S. (1981). Effective size and defendant bias in eyewitness identification lineups. Law and Human Behavior, 5(4), 299-309.

Tredoux, C. G. (1998). Statistical inference on measures of lineup fairness. Law and Human Behavior, 22(2), 217-237.

See also

lineup_table for a tabulation that shows null foils, and simulate_lineup_data, which records lineup_member directly.

Examples

# Raw choices from an 8-person lineup in which the suspect stands at
# position 3; 0 records a rejection
trials <- data.frame(
  lineup_member = c(3, 0, 5, 3, 1, 0, 3, 7),
  suspect_pos   = 3
)

classify_lineup_choices(trials, k = 8)
#>   lineup_member suspect_pos identification
#> 1             3           3        suspect
#> 2             0           3         reject
#> 3             5           3         filler
#> 4             3           3        suspect
#> 5             1           3         filler
#> 6             0           3         reject
#> 7             3           3        suspect
#> 8             7           3         filler

# A suspect position common to every trial can be given as a number
classify_lineup_choices(
  data.frame(lineup_member = c(2, 0, 4)),
  suspect_col = 2
)
#>   lineup_member identification
#> 1             2        suspect
#> 2             0         reject
#> 3             4         filler