diag_ratio_T: Diagnosticty Ratio (Tredoux, 1998)

In r4lineups: Statistical Inference on Lineup Fairness

Description

Computes Wells's adjusted diagnosticity ratio for one lineup pair (see: Tredoux, 1998)

Usage

diag_ratio_T(lineup_pres, lineup_abs, pos_pres, pos_abs, k1, k2)

Arguments

lineup_pres	A numeric vector of lineup choices for a lineup in which the target was present
lineup_abs	A numeric vector of lineup choices for a lineup in which the target was absent
pos_pres	A scalar, representing target position in TP lineup. Must be declared by user
pos_abs	A scalar, representing target position in TA lineup. Must be declared by user
k1	Number of targets in TP lineup. Must be specified by user (scalar).
k2	Number of targets in TA lineup. Must be specified by user (scalar).

References

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

Malpass, R. S., Tredoux, C., & McQuiston-Surrett, D. (2007). Lineup construction and lineup fairness. In R. Lindsay, D. F. Ross, J. D. Read, & M. P. Toglia (Eds.), Handbook of Eyewitness Psychology, Vol. 2: Memory for people (pp. 155-178). Mahwah, NJ: Lawrence Erlbaum Associates.

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

Tredoux, C. (1999). Statistical considerations when determining measures of lineup size and lineup bias. Applied Cognitive Psychology, 13, S9-S26.

Wells, G. L.,Leippe, M. R., & Ostrom, T. M. (1979). Guidelines for empirically assessing the fairness of a lineup. Law and Human Behavior, 3(4), 285-293.

Examples

#Data:
lineup_pres <- round(runif(100, 1, 6))
lineup_abs <- round(runif(70, 1, 5))
pos_pres <- 3
pos_abs <- 5

#Call:
diag_ratio_T(lineup_pres, lineup_abs, pos_pres, pos_abs, 6, 5)
diag_ratio_T(lineup_pres, lineup_abs, 3, 5, 6, 5)

r4lineups documentation built on May 2, 2019, 7:10 a.m.