A signal-detection-based, dual-process interpretation of remember/know judgments

2009 ◽  
Author(s):  
John T. Wixted ◽  
Laura Mickes
Keyword(s):  
Signal Detection ◽  
Dual Process

scholarly journals Eyewitness decisions in simultaneous and sequential lineups: A dual-process signal detection theory analysis

2005 ◽  
Vol 33 (5) ◽  
pp. 783-792 ◽  
Author(s):  
Christian A. Meissner ◽  
Colin G. Tredoux ◽  
Janat F. Parker ◽  
Otto H. MacLin
Keyword(s):  
Signal Detection ◽  
Signal Detection Theory ◽  
Detection Theory ◽  
Dual Process ◽  
Theory Analysis ◽  
Sequential Lineups

scholarly journals Evidence for the Contribution of A Threshold Retrieval Process to Semantic Memory

2017 ◽  
Vol 70 (10) ◽  
pp. 2026-2047 ◽  
Author(s):  
Maria Kempnich ◽  
Josephine A. Urquhart ◽  
Akira R. O'Connor ◽  
Chris J.A. Moulin
Keyword(s):  
Signal Detection ◽  
Semantic Memory ◽  
Target Identification ◽  
Dual Process ◽  
Semantic Retrieval ◽  
Retrieval Process ◽  
Operating Characteristics ◽  
Semantic Task ◽  
Unequal Variance ◽  
Detection Model

It is widely held that episodic retrieval can recruit two processes: a threshold context retrieval process (recollection) and a continuous signal strength process (familiarity). Conversely the processes recruited during semantic retrieval are less well specified. We developed a semantic task analogous to single-item episodic recognition to interrogate semantic recognition receiver-operating characteristics (ROCs) for a marker of a threshold retrieval process. We fitted observed ROC points to three signal detection models: two models typically used in episodic recognition (unequal variance and dual-process signal detection models) and a novel dual-process recollect-to-reject (DP-RR) signal detection model that allows a threshold recollection process to aid both target identification and lure rejection. Given the nature of most semantic questions, we anticipated the DP-RR model would best fit the semantic task data. Experiment 1 (506 participants) provided evidence for a threshold retrieval process in semantic memory, with overall best fits to the DP-RR model. Experiment 2 (316 participants) found within-subjects estimates of episodic and semantic threshold retrieval to be uncorrelated. Our findings add weight to the proposal that semantic and episodic memory are served by similar dual-process retrieval systems, though the relationship between the two threshold processes needs to be more fully elucidated.

scholarly journals Bias effects in a two-stage recognition paradigm: A challenge for ‘pure’ threshold and signal detection models

2021 ◽  
Author(s):  
Qiuli Ma ◽  
Jeffrey Joseph Starns ◽  
David Kellen
Keyword(s):  
Signal Detection ◽  
Forced Choice ◽  
Dual Process ◽  
High Threshold ◽  
Word Target ◽  
Choice Data ◽  
Two Stage ◽  
Unequal Variance ◽  
Single Item

We explored a two-stage recognition memory paradigm in which people first make single-item “studied”/“not studied” decisions and then have a chance to correct their errors in forced-choice trials. Each forced-choice trial included one studied word (“target”) and one non-studied word (“lure”) that received the same previous single-item response. For example, a “studied”-“studied” trial would have a target that was correctly called “studied” and a lure that was incorrectly called “studied.” The two-high-threshold (2HT) model and the unequal-variance signal detection (UVSD) model predict opposite effects of biasing the initial single-item responses on subsequent forced-choice accuracy. Results from two experiments showed that the bias effect is actually near zero and well out of the range of effects predicted by either model. Follow-up analyses showed that the model failures were not a function of experiment artifacts like changing memory states between the two types of recognition trials. Follow-up analyses also showed that the dual process signal detection (DPSD) model made better predictions for the forced-choice data than 2HT and UVSD models.

Modeling Guessing

2009 ◽  
Vol 217 (3) ◽  
pp. 125-135 ◽  
Author(s):  
Francis S. Bellezza
Keyword(s):  
Signal Detection ◽  
Source Monitoring ◽  
Dual Process ◽  
Process Dissociation ◽  
New Approach ◽  
Detection Model ◽  
Multinomial Processing Tree ◽  
Monitoring Model ◽  
Tree Modeling ◽  
Different Levels

Multinomial processing-tree modeling has had a major impact on process-dissociation theory. Buchner, Erdfelder, and Vaterrodt-Plünnecke (1995) added guessing parameters to the original model of Jacoby (1991) and created a class of process-dissociation models. Furthermore, Erfelder and Buchner (1998) formulated criterion values of the dual-process signal-detection model ( Yonelinas, 1994 ) as multinomial parameters. Buchner, Erdfelder, Steffens, and Martensen (1997) suggested a new approach by proposing a multinomial source-monitoring model for process-dissociation data. Two experiments described here demonstrated that dual-process signal-detection theory must assume different levels of familiarity in inclusion and exclusion tests. Similarly, in some cases the source-monitoring model must assume different levels of recognition guessing in the two tests. Reasons are given for preferring the source-monitoring model.

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