Kellen David, Klauer Karl Christoph (2020), Selecting amongst multinomial models: An apologia for normalized maximum likelihood, in Journal of Mathematical Psychology
, 97, 102367-102367.
Singmann Henrik, Kellen David (2019), New Methods in Cognitive Psychology
, Routledge, England, UK.
Skovgaard-Olsen Niels, Kellen David, Hahn Ulrike, Klauer Karl Christoph (2019), Norm conflicts and conditionals., in Psychological Review
, 126(5), 611-633.
Kellen David, Klauer Karl Christoph (2019), Theories of the Wason Selection Task: a Critical Assessment of Boundaries and Benchmarks, in Computational Brain & Behavior
Spektor Mikhail S., Kellen David (2018), The relative merit of empirical priors in non-identifiable and sloppy models: Applications to models of learning and decision-makingEmpirical priors, in Psychonomic Bulletin & Review
, 25(6), 2047-2068.
Trippas Dries, Kellen David, Singmann Henrik, Pennycook Gordon, Koehler Derek J., Fugelsang Jonathan A., Dubé Chad (2018), Characterizing belief bias in syllogistic reasoning: A hierarchical Bayesian meta-analysis of ROC data, in Psychonomic Bulletin & Review
, 25(6), 2141-2174.
Boehm Udo, Annis Jeffrey, Frank Michael J., Hawkins Guy E., Heathcote Andrew, Kellen David, Krypotos Angelos-Miltiadis, Lerche Veronika, Logan Gordon D., Palmeri Thomas J., van Ravenzwaaij Don, Servant Mathieu, Singmann Henrik, Starns Jeffrey J., Voss Andreas, Wiecki Thomas V., Matzke Dora, Wagenmakers Eric-Jan (2018), Estimating across-trial variability parameters of the Diffusion Decision Model: Expert advice and recommendations, in Journal of Mathematical Psychology
, 87, 46-75.
Kellen David, Singmann Henrik, Batchelder William H. (2018), Classic-probability accounts of mirrored (quantum-like) order effects in human judgments., in Decision
, 5(4), 323-338.
Spektor Mikhail S., Kellen David, Hotaling Jared M. (2018), When the Good Looks Bad: An Experimental Exploration of the Repulsion Effect, in Psychological Science
, 29(8), 1309-1320.
Klauer Karl Christoph, Kellen David (2018), RT-MPTs: Process models for response-time distributions based on multinomial processing trees with applications to recognition memory, in Journal of Mathematical Psychology
, 82, 111-130.
KellenDavid, SingmannHenrik, ChenSharon (2018), Assumption Violations in Forced-Choice Recognition Judgments: Implications from the Area Theorem., in CogSci
, Cognitive Science Society, United States of America.
Kellen David, Singmann Henrik (2017), Memory representations, tree structures, and parameter polysemy: Comment on Cooper, Greve, and Henson (2017), in Cortex
, 96, 148-155.
Skovgaard-Olsen Niels, Kellen David, Krahl Hannes, Klauer Karl Christoph (2017), Relevance differently affects the truth, acceptability, and probability evaluations of “and”, “but”, “therefore”, and “if–then”, in Thinking & Reasoning
, 23(4), 449-482.
A long-standing question in the domain of recognition memory concerns the nature of the representations that underlie our judgments when attempting to identify previously experienced stimuli or events (for reviews, see Malmberg, 2008; Wixted, 2007; Yonelinas & Parks, 2007). One hypothesis is that these representations are discrete, in the sense that an individual can only be in one of a few possible mental states, some of them being associated with successful memory retrieval, others with the complete absence or loss of memory information (e.g., Bröder & Schütz, 2009). Another hypothesis is that memory representations are continuous, reflecting a graded decay. The memory strength or familiarity associated with these representations is then compared to a response criterion that determines whether that level of memory strength or familiarity associated with the to-be-recognized stimuli or events is sufficient for them to be considered “old” (e.g., Wixted, 2007). A third possibility is a hybrid of the previous hypotheses and assumes the existence of two independent memory representations, a continuous process describing non-specific feelings of familiarity, and a discrete process associated with the retrieval of episodic content. A well-known example of the distinction between the two representations in this hybrid hypothesis is given by Mandler (1980), who describes the common situation of encountering somebody (e.g., a man in the bus) who feels quite familiar to him but no episodic details that could justify this familiarity can be recalled. At some later point in time, this episodic information finally becomes available (e.g., it was the butcher from the supermarket).In order to rigorously compare these different hypotheses, it is necessary to identify the behavioral data for which they make distinct predictions. Traditionally, comparisons between these three hypotheses have relied on the Receiver Operating Characteristics (ROC) functions that can be extracted from recognition judgments across different levels of response bias or confidence. Despite considerable efforts in the last decades, there is still no resolution in this debate (Yonelinas & Parks, 2007). One reason for this unfortunate state of affairs is that much of the ROC data are non-diagnostic, unless strong (and questionable) auxiliary assumptions are imposed (e.g., Malmberg, 2002). Such a requirement indicates that new approaches need to be developed. The goal of the present project is to make a contribution in this direction, by focusing on data and methods that have not been explored in the literature so far. A key notion in this project (which follows recent work by Kellen and Klauer, 2014, 2015) is that models instantiating these different representations can be compared by means of simple predictions that emerge from their core principles. Because these predictions are derived under fairly weak assumptions, they carry greater weight than traditional analyses comparing complex models predicated on strong and somewhat arbitrary distributional assumptions.The project is composed of four subprojects, each comparing distinct sets of model predictions. Although each subproject focuses on distinct issues, they complement each other by providing a broader picture regarding the limits of what each kind of representation can account for: Subproject 1 relies on strength-study manipulations in order to test whether the memory representations underlying ranking and confidence-ratings judgments are compatible with discrete or continuous memory representations. Subproject 2 provides a more detailed characterization of confidence-rating judgments, focusing on an overlooked signature effect of discrete-state representations when a response-bias shift takes place (e.g., Balakrishnan & Macdonald, 2002). Subproject 3 tests whether experimental factors expected to selective influence the components of hybrid representations yield data that cannot be accounted for by a unidimensional continuous model. Subproject 4 focuses on some of the fundamental constraints that hold for a unidimensional continuous model in forced-choice tasks.