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Ln of Diagnosticity Ratio

Source: R/ln_diag_ratio.R
ln_diag_ratio.Rd

Computes ln of diagnosticity ratio: ln(d)

Usage

ln_diag_ratio(linedf, correction = TRUE)

Arguments

linedf

A dataframe of parameters for computing diagnosticity ratio

correction

Logical. Apply Tredoux's small-cell correction (default TRUE). Set to FALSE for the uncorrected log relative risk used by the homogeneity procedure, which requires positive suspect-ID counts.

Details

The correction adds 0.5 to each suspect-identification count and to its corresponding sample total before computing the ratio: $$d = \frac{(n_{11}+0.5)/(n_{11}+n_{21}+0.5)}{(n_{12}+0.5)/(n_{12}+n_{22}+0.5)}$$ \(\ln(d)\) is then returned. The correction avoids undefined log ratios when a cell count is zero and stabilises variance estimates in small samples.

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

  • n22: Number of mock witnesses who did not identify the suspect in the target absent condition

References

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.

Examples

#Target present data:
A <- rep(1:6, length.out = 100)
B <- rep(1:5, length.out = 70)
C <- rep(1:4, length.out = 20)
lineup_pres_list <- list(A, B, C)
rm(A, B, C)


#Target absent data:
A <- rep(6:1, length.out = 100)
B <- rep(5:1, length.out = 70)
C <- rep(4:1, length.out = 20)
lineup_abs_list <- list(A, B, C)
rm(A, B, C)

# Suspect position for each TP/TA pair
pos_list <- c(3, 2, 1)

#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:
lnd <- ln_diag_ratio(linedf)