Description Usage Arguments Details Value References Examples
Function for computing Effective Size (Tredoux, 1998) on lineups contained as columns in a df, usually from a bootstrapped sample
1 | gen_esize_m(lineup_boot_df, k)
|
lineup_boot_df |
A dataframe containing bootstrapped samples of lineup data |
k |
Number of members in lineup. Must be specified by user (scalar). |
This function computes effective size for k lineups simultaneously.
A vector of effective size calculations for each lineup in bootstrapped df
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.
1 2 3 4 5 6 | #Data:
lineup_vec <- round(runif(100,1,6))
bootdf <- gen_boot_samples(lineup_vec, 1000)
#Call:
esize_vec <- gen_esize_m(bootdf, 6)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.