Compare Multi-d' Indices Between Two Conditions — compare

Computes the difference (x minus y) on every Multi-d' index, for example simultaneous versus sequential lineups, or high- versus low-similarity lineups. When both objects carry bootstrap draws, standard errors, percentile intervals and normal-approximation p-values are given for each difference. The two conditions are treated as independent samples: the standard error is the square root of the sum of the two bootstrap variances, and the interval is taken from differences between randomly re-paired draws, so the result does not depend on whether the two fits used the same seed.

Usage

compare_multid(x, y, labels = c("x", "y"), seed = NULL)

Arguments

x, y: Objects of class "multid" from make_multid, fitted with the same filler_rate.
labels: Names for the two conditions.
seed: Optional random seed for re-pairing the bootstrap draws.

Value

A data frame of class "multid_comparison".

Examples

# Simultaneous vs sequential lineups, Lee & Penrod's (2019) Table 3
sim <- make_multid(counts = c(G = 52, Fp = 25, Rp = 24, I = 28, Fa = 26, Ra = 46),
                   correction = "none")
sqn <- make_multid(counts = c(G = 44, Fp = 19, Rp = 39, I = 15, Fa = 17, Ra = 68),
                   correction = "none")
compare_multid(sim, sqn, labels = c("simultaneous", "sequential"))
#> Multi-d' comparison: simultaneous minus sequential
#> 
#>        index simultaneous sequential difference
#>           GI        0.620      0.864     -0.243
#>          GFp        0.720      0.719      0.001
#>          IFa        0.061     -0.082      0.143
#>         FaFp        0.039     -0.062      0.101
#>         RaRp        0.614      0.767     -0.153
#>      tp_bias        0.106     -0.048      0.154
#>    siphoning        0.659      0.801     -0.142
#>  ifa_vs_fair        1.276      0.908      0.367