Statistical Inference on Lineup Fairness
Confidence Intervals for Proportion
Bias for each lineup member
Lineup proportion for all lineup members
Chi-squared estimate of homogeneity of diagnosticity ratio
Comparing Effective Size: Base function for bootstrapping
Mean diagnosticity ratio for k lineup pairs
Diagnosticity ratio weights
Helper function
Helper function
Helper function
Parameters for diagnosticity ratio
Diagnosticty Ratio (Tredoux, 1998)
Diagnosticity Ratio (Wells & Lindsay, 1980; Wells & Turtle, 1986)
Effective Size per Foils
Master Function: Comparing Effective Size
Effective Size
Bootstrapped Effective Size
Effective Size (Tredoux, 1998)
Bootstrapped Effective Size (Tredoux, 1998)
Effective Size with Confidence Intervals from Normal Theory (Tredoux, ...
Compute similarity of faces in a lineup; experimental function
Bootstrapped Functional Size
Functional Size
Functional Size with Bootstrapped Confidence Intervals
Percentile of Bootstrapped Lineup Proportion
Descriptive statistics for bootstrapped lineup proportion
Bootstrap resampling
Bootstrapped resampling
Effective Size (across a dataframe)
Bootstrapped Confidence Intervals for Effective Size
Lineup proportion over dataframe
Lineup vector
Master function: Homogeneity of diagnosticity ratio
Homogeneity of diagnosticity ratio with bootstrapped CIs
I Component of Effective Size(Tredoux, 1998)
Confidence intervals for lineup proportion
Bootstrapped lineup proportion
Lineup proportion
Lineup proportion
Ln of Diagnosticity Ratio
Compute and plot ROC curve for lineup accuracy ~ confidence
Helper functions: Compute and plot ROC curve for lineup accuracy ~ con...
Helper functions
Rep index
Rotate vector
Helper function
Variance of diagnosticity ratio (Tredoux)
Variance of ln of diagnosticity ratio
Since the early 1970s eyewitness testimony researchers have recognised the importance of estimating properties such as lineup bias (is the lineup biased against the suspect, leading to a rate of choosing higher than one would expect by chance?), and lineup size (how many reasonable choices are in fact available to the witness? A lineup is supposed to consist of a suspect and a number of additional members, or foils, whom a poor-quality witness might mistake for the perpetrator). Lineup measures are descriptive, in the first instance, but since the earliest articles in the literature researchers have recognised the importance of reasoning inferentially about them. This package contains functions to compute various properties of laboratory or police lineups, and is intended for use by researchers in forensic psychology and/or eyewitness testimony research. Among others, the r4lineups package includes functions for calculating lineup proportion, functional size, various estimates of effective size, diagnosticity ratio, homogeneity of the diagnosticity ratio, ROC curves for confidence x accuracy data and the degree of similarity of faces in a lineup.