TY - JOUR
T1 - The ignored alternative
T2 - An application of Luce's low-threshold model to recognition memory
AU - Kellen, David
AU - Erdfelder, Edgar
AU - Malmberg, Kenneth J.
AU - Dubé, Chad
AU - Criss, Amy H.
N1 - Publisher Copyright:
© 2016
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Recent years have seen an increased interest in models of recognition memory's decision stage. However, only a relatively narrow set of candidate models has been considered thus far, with comparisons being typically restricted to signal detection and high-threshold models. Here, we consider a third alternative, Luce's (1963) low-threshold model (LTM). We evaluated the LTM's predictions for existing Yes–No receiver-operating characteristic data (Dube et al., 2012) as well as data from K-alternative ranking tasks (Kellen and Klauer, 2014). The LTM, which to this point has been largely ignored in the recognition memory literature, turns out to perform at least as well as the most popular model in this domain, the Gaussian signal detection model. These results suggest future work concerning the decision stage of recognition should consider the LTM in addition to the continuous and discrete-state models that have dominated the literature so far.
AB - Recent years have seen an increased interest in models of recognition memory's decision stage. However, only a relatively narrow set of candidate models has been considered thus far, with comparisons being typically restricted to signal detection and high-threshold models. Here, we consider a third alternative, Luce's (1963) low-threshold model (LTM). We evaluated the LTM's predictions for existing Yes–No receiver-operating characteristic data (Dube et al., 2012) as well as data from K-alternative ranking tasks (Kellen and Klauer, 2014). The LTM, which to this point has been largely ignored in the recognition memory literature, turns out to perform at least as well as the most popular model in this domain, the Gaussian signal detection model. These results suggest future work concerning the decision stage of recognition should consider the LTM in addition to the continuous and discrete-state models that have dominated the literature so far.
KW - High threshold models
KW - Low threshold models
KW - ROCs
KW - Recognition
KW - Signal detection theory
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U2 - 10.1016/j.jmp.2016.03.001
DO - 10.1016/j.jmp.2016.03.001
M3 - Article
AN - SCOPUS:84964882642
SN - 0022-2496
VL - 75
SP - 86
EP - 95
JO - Journal of Mathematical Psychology
JF - Journal of Mathematical Psychology
ER -