Testing the foundations of signal detection theory in recognition memory.

Kellen, David; Winiger, Samuel; Dunn, John C.; Singmann, Henrik

doi:10.1037/rev0000288

Cited by 45 publications

(106 citation statements)

References 152 publications

(374 reference statements)

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“…RRW’s critique is motivated by a strong concern with individual heterogeneity, a concern that I share with similar intensity (e.g., Kellen et al, 2016, 2017, 2020, 2021; Kellen & Klauer, 2020; Singmann & Kellen, 2019). Lest we forget: The reality of individual heterogeneity introduces serious inferential challenges, which researchers ignore at their own peril.…”

Section: Concluding Thoughtsmentioning

confidence: 99%

Behavioral decision research is not a Linda problem: Comment on Regenwetter et al. (2022).

Kellen¹

2022

Decision

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Regenwetter et al. (2022) argue that research on decision-making is plagued with conjunction fallacies or “Linda Effects.” As a case study, they provide a critical analysis of Kahneman and Tversky’s seminal article on Prospect Theory and its 1992 sequel. This commentary evaluates their criticisms and ultimately finds them to be predicated on a number of misconceptions. As argued below, a reliance on stylized effects at the aggregate level is perfectly legitimate when dismissing a received view and first proposing a new account that organizes said effects in theoretically-meaningful ways.

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Section: Concluding Thoughtsmentioning

confidence: 99%

Behavioral decision research is not a Linda problem: Comment on Regenwetter et al. (2022).

Kellen¹

2022

Decision

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“…SDT is arguably one of the greatest success stories in modern psychological research, with its application to recognition memory being a particularly notable example (for recent overviews, see Kellen & Klauer, 2018 ; Kellen et al, 2021 ; Rotello, 2019; Wixted, 2020 ). In light of this success, nobody should be surprised to see its application being regularly extended to new domains.…”

Section: Discussionmentioning

confidence: 99%

“…When searching for ways to obtain more informative lineup data, researchers are strongly encouraged to capitalize on SDT’s impressive track record in linking different types of judgments (see Gepshtein et al, 2020 ; Kellen et al, 2021 ; Meyer-Grant & Klauer, 2021 ). For example, Kellen et al ( 2012 ) relied on the close relationship between ranking and yes-no recognition judgments to estimate criterion noise under minimal assumptions (for other examples of joint modeling, see Rouder & Batchelder, 1998 ; Chechile, 2004 , Jang et al, 2009 ).…”

Section: Discussionmentioning

confidence: 99%

Toward a more comprehensive modeling of sequential lineups

Kellen

McAdoo

2022

Cogn. Research

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Sequential lineups are one of the most commonly used procedures in police departments across the USA. Although this procedure has been the target of much experimental research, there has been comparatively little work formally modeling it, especially the sequential nature of the judgments that it elicits. There are also important gaps in our understanding of how informative different types of judgments can be (binary responses vs. confidence ratings), and the severity of the inferential risks incurred when relying on different aggregate data structures. Couched in a signal detection theory (SDT) framework, the present work directly addresses these issues through a reanalysis of previously published data alongside model simulations. Model comparison results show that SDT modeling can provide elegant characterizations of extant data, despite some discrepancies across studies, which we attempt to address. Additional analyses compare the merits of sequential lineups (with and without a stopping rule) relative to showups and delineate the conditions in which distinct modeling approaches can be informative. Finally, we identify critical issues with the removal of the stopping rule from sequential lineups as an approach to capture within-subject differences and sidestep the risk of aggregation biases.

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“…The 2HT and UVSD models have been pitted against each other in a number of different studies (for example, Bröder & Schütz, 2009; Chechile, 2013; Chen et al, 2015; Dube & Rotello, 2012; Dube et al, 2012; Kellen & Klauer, 2014, 2015; Kellen et al, 2013; Kellen & Klauer, 2015; Province & Rouder, 2012; Starns et al, 2018; Starns & Ma, 2018; Voormann et al, 2021). However, whereas earlier comparisons mostly focused on goodness-of-fit indices (corrected for model flexibility) associated with receiver-operating characteristic (ROC) functions, more recent work has targeted specific qualitative differences between the models (for a discussion on “critical testing,” see Kellen et al, 2021). The present work continues this recent trend.…”

Section: Model Overviewmentioning

confidence: 99%

Bias effects in a two-stage recognition paradigm: A challenge for “pure” threshold and signal detection models.

Ma¹,

Starns²,

Kellen³

2022

Journal of Experimental Psychology: Learning, Memory, and Cogni

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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. Bias Effects 3Bias effects in a two-stage recognition paradigm: A challenge for 'pure' threshold and signal detection models A popular way to test memory ability is to ask someone to discriminate stimuli that were encountered in a target context from those that were not, such as deciding whether or not a certain word was studied in a previous list. This procedure, known as a recognition task, has been influential in both applied research (e.g.,

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Testing the foundations of signal detection theory in recognition memory.

Abstract: and two anonymous reviewers for valuable comments. Portions of this work were presented at the 59th Annual Meeting of the Psychonomic Society, the 2019 Context and Episodic Memory Symposium (CEMS), and at the 52nd Annual Meeting of the Society for Mathematical Psychology.

Cited by 45 publications

References 152 publications

Behavioral decision research is not a Linda problem: Comment on Regenwetter et al. (2022).

Behavioral decision research is not a Linda problem: Comment on Regenwetter et al. (2022).

Toward a more comprehensive modeling of sequential lineups

Bias effects in a two-stage recognition paradigm: A challenge for “pure” threshold and signal detection models.

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