func_size_report: Functional Size with Bootstrapped Confidence Intervals

In r4lineups: Statistical Inference on Lineup Fairness

Description

This function is a master function, calling other functions it needs, and reporting results in some detail

Usage

func_size_report(lineup_vec, target_pos, k, R)

Arguments

lineup_vec	A numeric vector of lineup choices
target_pos	A scalar, representing target position in lineup. Must be declared by user
k	Number of members in lineup. Must be specified by user (scalar).
R	Number of bootstrap samples. Defaults to 1000

Details

Function depends on functions from package 'boot'

References

Davison, A.C. & Hinkley, D.V. (1997). Bootstrap methods and their application. Cambridge University Press.

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.

See Also

boot: https://cran.r-project.org/web/packages/boot/boot.pdf

Examples

#Data:
lineup_vec <- round(runif(100, 1, 6))
target_pos <- 3

#Call:
x <- func_size_report(lineup_vec, target_pos, 6)
x <- func_size_report(lineup_vec, 3, 6)

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