Skip to contents

Standardize Lineup Identification Data

Source: R/data_standardization.R
standardize_lineup_data.Rd

Converts lineup data from various formats into the standardized r4lineups format. Handles common data issues and ensures compatibility with all confidence-based analyses.

Usage

standardize_lineup_data(
  data,
  target_present_col = "target_present",
  identification_col = "identification",
  confidence_col = "confidence",
  response_time_col = NULL,
  participant_id_col = NULL,
  recode_identification = NULL,
  validate = TRUE
)

Arguments

data

A data frame with lineup identification data

target_present_col

Name of column indicating target presence (default = "target_present"). Can also be "tp", "culprit_present", etc.

identification_col

Name of column with identification responses (default = "identification"). Can also be "response", "choice", etc.

confidence_col

Name of column with confidence ratings (default = "confidence"). Can also be "conf", "certainty", etc.

response_time_col

Name of column with response times (optional)

participant_id_col

Name of column with participant IDs (optional)

recode_identification

Named character vector for recoding identification values. E.g., c("target" = "suspect", "foil" = "filler")

validate

Logical. Whether to validate the result (default = TRUE)

Value

A standardized data frame with class "lineup_data" containing:

  • target_present: Logical

  • identification: Character ("suspect", "filler", "reject")

  • confidence: Numeric (if present)

  • participant_id: Original or generated (if present)

  • response_time: Numeric (if present)

followed by every other column of data unchanged, including suspect_pos and lineup_member, which some analyses use.

Details

This function:

  • Renames columns to standard names

  • Converts data types as needed

  • Recodes identification values to standard terms

  • Adds participant IDs if missing

  • Validates the result (if validate = TRUE)

  • Adds S3 class "lineup_data"

**Common recoding patterns:**

  • "target" → "suspect"

  • "foil" / "distractor" → "filler"

  • "none" / "not present" / "no choice" → "reject"

Examples

# Data with non-standard column names
raw_data <- data.frame(
  tp = c(1, 1, 0, 0),
  response = c("target", "foil", "none", "target"),
  conf = c(5, 3, 2, 4)
)

# Standardize
std_data <- standardize_lineup_data(
  raw_data,
  target_present_col = "tp",
  identification_col = "response",
  confidence_col = "conf",
  recode_identification = c(
    "target" = "suspect",
    "foil" = "filler",
    "none" = "reject"
  )
)
#> Warning: Very small sample size (n=4). Results may be unreliable.
print(std_data)
#> 
#> === Standardized Lineup Data ===
#> 
#> Format: r4lineups standard format
#> Rows: 4 
#> Columns: target_present, identification, confidence, participant_id 
#> 
#> Target-present trials: 2 
#> Target-absent trials: 2 
#> 
#> Identifications:
#>   filler    : 1
#>   reject    : 1
#>   suspect   : 2
#> 
#> Confidence range: 2 to 5 
#> 
#> First 10 rows:
#>   target_present identification confidence participant_id
#> 1           TRUE        suspect          5              1
#> 2           TRUE         filler          3              2
#> 3          FALSE         reject          2              3
#> 4          FALSE        suspect          4              4