d_weights: Diagnosticity ratio weights

In tmnaylor/r4lineups: Statistical Inference on Lineup Fairness

Description

Function to compute weights of each diagnosticity ratio for k lineup pairs

Usage

d_weights(linedf)

Arguments

linedf

A dataframe of parameters for computing diagnosticity ratio

Details

In order to obtain a pooled estimate of a set of diagnosticity ratios, we use a weight for each ratio that is equal to the inverse of its variance.

To get linedf, use the diag_param helper function

diag_param returns a dataframe containing the following:

• n11: Number of mock witnesses who identified the suspect in the target present condition

• n21: Number of mock witnesses who did not identify the suspect in the target present condition

• n12: Number of mock witnesses who identified the suspect in the target absent condition

• n13: Number of mock witnesses who did not identify the suspect in the target absent condition

Value

A dataframe with one column containing weights for each pair of lineups for which diagnosticity ratio is being calculated.

References

Tredoux, C. G. (1998). Statistical inference on measures of lineup fairness. Law and Human Behavior, 22(2), 217-237.

Examples

#Target present data:
A <-  round(runif(100,1,6))
B <-  round(runif(70,1,5))
C <-  round(runif(20,1,4))
lineup_pres_list <- list(A, B, C)
rm(A, B, C)


#Target absent data:
A <-  round(runif(100,1,6))
B <-  round(runif(70,1,5))
C <-  round(runif(20,1,4))
lineup_abs_list <- list(A, B, C)
rm(A, B, C)

#Pos list
lineup1_pos <- c(1, 2, 3, 4, 5, 6)
lineup2_pos <- c(1, 2, 3, 4, 5)
lineup3_pos <- c(1, 2, 3, 4)
pos_list <- list(lineup1_pos, lineup2_pos, lineup3_pos)
rm(lineup1_pos, lineup2_pos, lineup3_pos)

#Nominal size:
k <- c(6, 5, 4)

#Use diag param helper function to get data (n11, n21, n12, n22):
linedf <- diag_param(lineup_pres_list, lineup_abs_list, pos_list, k)

#Call:
wi <- d_weights(linedf)

tmnaylor/r4lineups documentation built on May 10, 2019, 8:30 a.m.