Results 11 to 20 of about 3,569 (224)
HMMTree: A computer program for latent-class hierarchical multinomial processing tree models [PDF]
Behavior Research Methods, 2007 Latent-class hierarchical multinomial models are an important extension of the widely used family of multinomial processing tree models, in that they allow for testing the parameter homogeneity assumption and provide a framework for modeling parameter heterogeneity.
Christoph Stahl +2 more
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Using recursive partitioning to account for parameter heterogeneity in multinomial processing tree models [PDF]
Behavior Research Methods, 2017 In multinomial processing tree (MPT) models, individual differences between the participants in a study can lead to heterogeneity of the model parameters. While subject covariates may explain these differences, it is often unknown in advance how the parameters depend on the available covariates, that is, which variables play a role at all, interact, or
Achim Zeileis, Zeileis Achim
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Effect of delay interval and cue focality on prospective memory [PDF]
BMC PsychologyBackground Prospective memory refers to the ability to perform planned things in the appropriate future situations. Due to pointing towards the future, prospective memory usually has a certain amount of time delay. This study investigated the impact of a
Zongbin Sun +5 more
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Parametric order constraints in multinomial processing tree models: An extension of Knapp and Batchelder (2004) [PDF]
Journal of Mathematical Psychology, 2015 Multinomial processing tree (MPT) models are tools for disentangling the contributions of latent cognitive processes in a given experimental paradigm. The present note analyzes MPT models subject to order constraints on subsets of its parameters. The constraints that we consider frequently arise in cases where the response categories are ordered in ...
Karl Christoph Klauer +2 more
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Investigating the Social Boundaries of Fairness by Modeling Ultimatum Game Responders’ Decisions with Multinomial Processing Tree Models [PDF]
GamesFairness in competitive games such as the Ultimatum Game is often defined theoretically. According to some of the literature, in which fairness is determined only based on resource allocation, a proposal splitting resources evenly (i.e., 5:5) is ...
Marco Biella, Max Hennig, Laura Oswald
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A Multinomial Processing Tree Model of RC Attachment [PDF]
Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics, 2021 In the field of sentence processing, speakers’ preferred interpretation of ambiguous sentences is often determined using a variant of a discrete choice task, in which participants are asked to indicate their preferred meaning of an ambiguous sentence. We discuss participants’ degree of attentiveness as a potential source of bias and variability in such
Pavel Logacev, Noyan Dokudan
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On Aggregation Invariance of Multinomial Processing Tree Models
Behavior Research Methods, 2023 Multinomial processing tree (MPT) models are prominent and frequently used tools to model and measure cognitive processes underlying responses in many experimental paradigms. Although MPT models typically refer to cognitive processes within single individuals, they have often been applied to group data aggregated across individuals.
Erdfelder, Edgar +2 more
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On the role of recognition in consumer choice: A model comparison [PDF]
Judgment and Decision Making, 2014 One prominent model in the realm of memory-based judgments and decisions is the recognition heuristic. Under certain preconditions, it presumes that choices are based on recognition in a one-cue non-compensatory manner and that other information is ...
Benjamin E. Hilbig
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Parameter identification in multinomial processing tree models [PDF]
Behavior Research Methods, 2010 Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis of the likelihood function, and for the ...
Schmittmann, V.D. +3 more
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ABrox-A user-friendly Python module for approximate Bayesian computation with a focus on model comparison. [PDF]
PLoS ONE, 2018 We give an overview of the basic principles of approximate Bayesian computation (ABC), a class of stochastic methods that enable flexible and likelihood-free model comparison and parameter estimation.
Ulf Kai Mertens +2 more
doaj +1 more source