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Bayesian Comparison of Two Diagnosticity Ratios

Source: R/diag_ratio_T_bayes.R
diag_ratio_T_bayes_compare.Rd

Fits independent Beta-Binomial models to two lineup pairs and returns the posterior distribution of the difference \(\Delta = DR_A - DR_B\), together with \(P(DR_A > DR_B \mid \mathbf{n})\).

Usage

diag_ratio_T_bayes_compare(
  pres_A,
  abs_A,
  pos_pres_A,
  pos_abs_A,
  k1_A,
  k2_A,
  pres_B,
  abs_B,
  pos_pres_B,
  pos_abs_B,
  k1_B,
  k2_B,
  alpha = 0.5,
  S = 10000,
  credible_mass = 0.95
)

Arguments

pres_A, abs_A

Numeric vectors of lineup choices for lineup pair A (target-present and target-absent, respectively).

pos_pres_A, pos_abs_A

Suspect positions for pair A.

k1_A, k2_A

Lineup sizes for pair A (for validation).

pres_B, abs_B

Numeric vectors of lineup choices for lineup pair B.

pos_pres_B, pos_abs_B

Suspect positions for pair B.

k1_B, k2_B

Lineup sizes for pair B.

alpha

Prior concentration (shared). Default 0.5 (Jeffreys).

S

Number of posterior draws. Default 10000.

credible_mass

Width of credible interval. Default 0.95.

Value

An object of class "diag_ratio_T_bayes_compare".

See also

diag_ratio_T_bayes

Examples

set.seed(1)
pres_A <- round(runif(100, 1, 6)); abs_A <- round(runif(80, 1, 6))
pres_B <- round(runif(100, 1, 6)); abs_B <- round(runif(80, 1, 6))
res <- diag_ratio_T_bayes_compare(pres_A, abs_A, 3, 3, 6, 6,
                                   pres_B, abs_B, 3, 3, 6, 6)
print(res)
#> Bayesian comparison of diagnosticity ratios (DR_A - DR_B)
#>   DR_A posterior mean: 1.368
#>   DR_B posterior mean: 0.914
#>   Delta posterior mean:   0.454
#>   Delta posterior median: 0.421
#>   95% CI on delta: [-0.370, 1.445]
#>   P(DR_A > DR_B | data): 0.8532
#>   P(DR_B > DR_A | data): 0.1468