Bird diversity hot spots in a recovering subtropical forest do not align with protected area zoning, instead occurring in experimental zones with low‐intensity human activity. This mismatch is driven by contrasting responses: Abundant core species are supported by productivity, while many species of low frequency are attracted to the habitat ...
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Identification of discriminative plasma protein biomarkers for recent Mycobacterium tuberculosis infection: a pilot data‑independent acquisition mass spectrometry‑based proteomics study. [PDF]
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FeXAI: Federated and Explainable AI for cyber threat detection in IoT-enabled smart transportation systems. [PDF]
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Manipulating belief partially remedies the metamemory expectancy illusion in schema-based source monitoring. [PDF]
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Multinomial Processing Tree Models
Zeitschrift Fuer Psychologie Mit Zeitschrift Fuer Angewandte Psychologie, 2009Multinomial processing tree (MPT) models have become popular in cognitive psychology in the past two decades. In contrast to general-purpose data analysis techniques, such as log-linear models or other generalized linear models, MPT models are substantively motivated stochastic models for categorical data.
Edgar Erdfelder +2 more
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Sequential hypothesis tests for multinomial processing tree models
Journal of Mathematical Psychology, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Multinomial Processing Tree Models for Discrete Choice
Zeitschrift Fuer Psychologie Mit Zeitschrift Fuer Angewandte Psychologie, 2009This paper shows how to develop new multinomial processing tree (MPT) models for discrete choice, and in particular binary choice. First it reviews the history of discrete choice with special attention to Duncan Luce’s book Individual Choice Behavior. Luce’s choice axiom leads to the Bradley-Terry-Luce (BTL) paired-comparison model which is the basis ...
William H Batchelder, Xiangen Hu
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Hierarchical Multinomial Processing Tree Models: A Latent-Class Approach
Psychometrika, 2006Multinomial processing tree models are widely used in many areas of psychology. Their application relies on the assumption of parameter homogeneity, that is, on the assumption that participants do not differ in their parameter values. Tests for parameter homogeneity are proposed that can be routinely used as part of multinomial model analyses to defend
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