gen_esize_m: Effective Size (across a dataframe)

In r4lineups: Statistical Inference on Lineup Fairness

Description

Function for computing Effective Size (Tredoux, 1998) on lineups contained as columns in a df, usually from a bootstrapped sample

Usage

gen_esize_m(lineup_boot_df, k)

Arguments

lineup_boot_df	A dataframe containing bootstrapped samples of lineup data
k	Number of members in lineup. Must be specified by user (scalar).

Details

This function computes effective size for k lineups simultaneously.

Value

A vector of effective size calculations for each lineup in bootstrapped df

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_vec <- round(runif(100,1,6))
bootdf <- gen_boot_samples(lineup_vec, 1000)

#Call:
esize_vec <- gen_esize_m(bootdf, 6)

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