Estimate decision criterion (gamma) and discriminability (d') from rejection rates in culprit-absent and culprit-present lineups.
Usage
estimate_msdt_params(pr_rej_I, pr_rej_G, lineup_size, eps = 1e-06)
msdt_gamma_from_rej(pr_rej_I, lineup_size, eps = 1e-06)
msdt_dprime_from_rej(pr_rej_G, gamma, lineup_size, eps = 1e-06)Arguments
- pr_rej_I
Rejection rate in culprit-absent lineups.
- pr_rej_G
Rejection rate in culprit-present lineups.
- lineup_size
Lineup size (suspect + fillers), must be >= 2.
- eps
Small value used to avoid probabilities of 0 or 1.
- gamma
Decision criterion estimated from culprit-absent rejection rates, typically returned by
msdt_gamma_from_rej().
Details
This is a method-of-moments estimator that is exactly identified
from the two rejection rates alone: Pr(REJ|I) fixes gamma, and the gap
between culprit-absent and culprit-present rejection rates fixes d'. It is
information-lossy: it ignores the composition of choices
(suspect-ID vs filler-ID) and the spread of filler choices, which are the
most diagnostic outcomes. If you have the full response breakdown
(suspect/filler/reject counts for both lineup types), prefer the
minimum-Pearson fitter fit_max_sdt or the 2-HT model
(fit_winter_2ht), which use all outcome counts.
See also
fit_max_sdt for a full-outcome, minimum-Pearson fit;
fit_winter_2ht for the 2-HT MPT model.