Bayesian Estimation of Multinomial Processing Tree Models with Heterogeneity in Participants and Items [PDF]
Psychometrika, 2015 Multinomial processing tree (MPT) models are theoretically motivated stochastic models for the analysis of categorical data. Here we focus on a crossed-random effects extension of the Bayesian latent-trait pair-clustering MPT model. Our approach assumes that participant and item effects combine additively on the probit scale and postulates ...
Matzke, D. +3 more
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Bayesian modeling of the Mnemonic Similarity Task using multinomial processing trees
Behaviormetrika, 2023 The Mnemonic Similarity Task (MST: Stark et al., 2019) is a modified recognition memory task designed to place strong demand on pattern separation. The sensitivity and reliability of the MST make it an extremely valuable tool in clinical settings. We develop new cognitive models, based on the multinomial processing tree framework, for two versions of ...
Michael D. Lee, Craig E. L. Stark
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Differential patterns of planning impairments in Parkinson's disease and sub-clinical signs of dementia? A latent-class model-based approach. [PDF]
PLoS ONE, 2012 Planning impairments mark a well-documented consequence of neurodegenerative diseases such as Parkinson's disease (PD). Recently, using the Tower of London task we demonstrated that, rather than being generally impaired, PD patients selectively fail when
Lena Köstering +3 more
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Classification of Bugs in Cloud Computing Applications Using Machine Learning Techniques
Applied Sciences, 2023 In software development, the main problem is recognizing the security-oriented issues within the reported bugs due to their unacceptable failure rate to provide satisfactory reliability on customer and software datasets.
Nadia Tabassum +5 more
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Think or blink — is the recognition heuristic an “intuitive” strategy?
Judgment and Decision Making, 2010 Several approaches to judgment and decision making emphasize the effort-reducing properties of heuristics. One prominent example for effort-reduction is the recognition heuristic (RH) which proposes that judgments are made by relying on one single cue ...
Benjamin E. Hilbig +5 more
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Precise models deserve precise measures: A methodological dissection
Judgment and Decision Making, 2010 The recognition heuristic (RH) — which predicts non-compensatory reliance on recognition in comparative judgments — has attracted much research and some disagreement, at times.
Benjamin E. Hilbig +3 more
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Extending multinomial processing tree models to measure the relative speed of cognitive processes [PDF]
Psychonomic Bulletin & Review, 2016 Multinomial processing tree (MPT) models account for observed categorical responses by assuming a finite number of underlying cognitive processes. We propose a general method that allows for the inclusion of response times (RTs) into any kind of MPT model to measure the relative speed of the hypothesized processes.
Heck, Daniel W., Erdfelder, Edgar
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Sentiment Analysis of Product Reviews Using Fine-Tuned LLaMa-3 Model: Evaluation with Comprehensive Benchmark Metrics [PDF]
ITM Web of ConferencesSentiment analysis, a crucial subfield of natural language processing, enables businesses and policymakers to understand public emotions and opinions, essential for crafting effective strategies across industries like marketing and customer service.
Wang Yili
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A multinomial processing tree model for degradation and redintegration in immediate recall [PDF]
Memory & Cognition, 1993 When items are presented for immediate recall, a verbal trace is formed and degrades quickly, becoming useless after about 2 sec. The span for items such as digits equals the number of items that can be pronounced in the available time. The length of the items affects span by affecting pronunciation rate.
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Precise models deserve precise measures [PDF]
Judgment and Decision Making, 2010 The recognition heuristic (RH) --- which predicts non-compensatory reliance on recognition in comparative judgments --- has attracted much research and some disagreement, at times.
Benjamin E. Hilbig
doaj