line73

<p>A dataframe of lineup choices for 1 trial; real data from a Doob &amp; Kirshenbaum (1973) article.
            This article was the first to discuss lineup size
            1 column x 42 observations</p>
<p>42 mock witnesses
            Nominal size is 6
            Target position is 4</p>

datasets

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.

line73: line73

Description

Usage

Arguments

Format

References