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r4lineups  

Statistical Inference on Lineup Fairness
View on CRAN: Click here


Download and install r4lineups package within the R console
Install from CRAN:
install.packages("r4lineups")

Install from Github:
library("remotes")
install_github("cran/r4lineups")

Install by package version:
library("remotes")
install_version("r4lineups", "0.1.1")



Attach the package and use:
library("r4lineups")
Maintained by
Colin Tredoux
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-07-18
Latest Update: 2018-07-18
Description:
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.
How to cite:
Colin Tredoux (2018). r4lineups: Statistical Inference on Lineup Fairness. R package version 0.1.1, https://cran.r-project.org/web/packages/r4lineups. Accessed 18 Feb. 2025.
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Complete documentation for r4lineups
Functions, R codes and Examples using the r4lineups R package
Some associated functions: allfoil_cihigh . allfoilbias . allprop . chi_diag . compare_eff_sizes.boot . d_bar . d_weights . datacheck1 . datacheck2 . datacheck3 . diag_param . diag_ratio_T . diag_ratio_W . eff_size_per_foils . effsize_compare . esize_T . esize_T_boot . esize_T_ci_n . esize_m . esize_m_boot . face_sim . func_size.boot . func_size . func_size_report . gen_boot_propci . gen_boot_propmean_se . gen_boot_samples . gen_boot_samples_list . gen_esize_m . gen_esize_m_ci . gen_lineup_prop . gen_linevec . homog_diag . homog_diag_boot . i_esize_T . line73 . lineup_boot_allprop . lineup_prop_boot . lineup_prop_tab . lineup_prop_vec . ln_diag_ratio . make_roc . make_rocdata . makevec_prop . mickwick . mockdata . nortje2012 . rep_index . rot_vector . show_lineup . var_diag_ratio . var_lnd . 
Some associated R codes: allfoil_cis.R . allfoilbias.R . allprop.R . boot_helper.R . chi_diag.R . chi_diag.boot.R . compare_eff_sizes.boot.R . d_bar.R . d_bar.boot.R . d_weights.R . datacheck1.R . datacheck2.R . datacheck3.R . datacheck4.R . datacheck5.R . diag_param.R . diag_param_boot.R . diag_ratio_T.R . diag_ratio_W.R . eff_size_per_foils.R . effsize_compare.R . esize_T.R . esize_T_boot.R . esize_T_ci_n.R . esize_boot.R . esize_m.R . face.R . face_sim.R . func_size.R . func_size_boot.R . func_size_report.R . gen_boot_propci.R . gen_boot_propmean_se.R . gen_boot_samples.R . gen_boot_samples_list.R . gen_esize_m.R . gen_esize_m_ci.R . gen_lineup_prop.R . homog_diag.R . homog_diag_boot.R . i_esize_T.R . line73.R . lineup_boot_allprop.R . lineup_prop_boot.R . lineup_prop_tab.R . lineup_prop_vec.R . ln_diag_ratio.R . make_roc.R . mickwick.R . mockdata.R . nortje2012.R . rep_index.R . roc_functions.R . rot_vector.R . tab_to_vec.R . typecheck.R . var_d.R . var_lnd.R .  Full r4lineups package functions and examples
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