compare_eff_sizes.boot: Comparing Effective Size: Base function for bootstrapping
In r4lineups: Statistical Inference on Lineup Fairness

Description Usage Arguments Details References

A base function for bootstrapping a dataframe of choices for 2 independent lineups

1	compare_eff_sizes.boot(linedf, d)

`linedf`	A dataframe of lineup data. Must consist of 2 columns, each containing data for 2 independent lineups
`d`	Indices for bootstrap sample. Argument used by boot function to select samples for bootstrapping

The approach here is to compute the effective size of each lineup separately, and to take the difference between them. This is then bootstrapped, and if the bootstrap does not contain 0, we conclude the effective size estimates are different at p = alpha

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

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.

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