Consensus theory for mixed response formats
Publication date: October 2018Source: Journal of Mathematical Psychology, Volume 86Author(s): André AßfalgAbstractMeasuring shared beliefs, expert consensus, or the details of a crime in eyewitness testimony represents a psychometric challenge. In expert interviews, for example, the correct responses representing the expert consensus (i.e., the answer key) are initially unknown and experts may differ in their contribution to this consensus. I propose the variable-response model, an extension of latent-trait models. The model allows the estimation of the answer key and the latent trait for continuous, categorical, or mixe...
Source: Journal of Mathematical Psychology - September 20, 2018 Category: Psychiatry & Psychology Source Type: research
Editorial Board
Publication date: August 2018Source: Journal of Mathematical Psychology, Volume 85Author(s): (Source: Journal of Mathematical Psychology)
Source: Journal of Mathematical Psychology - September 12, 2018 Category: Psychiatry & Psychology Source Type: research
Editorial
Publication date: August 2018Source: Journal of Mathematical Psychology, Volume 85Author(s): Adele Diederich (Source: Journal of Mathematical Psychology)
Source: Journal of Mathematical Psychology - September 12, 2018 Category: Psychiatry & Psychology Source Type: research
Foresight, risk attitude, and utility maximization in naturalistic sequential high-stakes decision making
Publication date: October 2018Source: Journal of Mathematical Psychology, Volume 86Author(s): Zhiqin Chen, Richard S. JohnAbstractWe explore three research questions related to risky sequential choice: (1) Does adherence to expected utility theory increase or decrease over sequential choices? (2) Does risk attitude vary systematically over sequential choices? and (3) To what extent are sequential choices influenced by future possible choices? We selected the game show, Deal or No Deal (DOND), as a context to study sequential decision making under risk with high stakes. We obtained data from complete game episodes involving...
Source: Journal of Mathematical Psychology - September 9, 2018 Category: Psychiatry & Psychology Source Type: research
Expected Scott–Suppes utility representation
Publication date: October 2018Source: Journal of Mathematical Psychology, Volume 86Author(s): Nuh Aygün Dalkıran, Oral Ersoy Dokumacı, Tarık KaraAbstractWe provide an axiomatic characterization for an expected Scott–Suppes utility representation. Such a characterization is the natural analog of the von Neumann–Morgenstern expected utility theorem for semiorders and it is noted as an open problem by Fishburn (1968). Expected Scott–Suppes utility representation is analytically tractable and can be used in applications that study preferences with intransitive indifference under uncertainty. Our representation offers...
Source: Journal of Mathematical Psychology - August 31, 2018 Category: Psychiatry & Psychology Source Type: research
A better (Bayesian) interval estimate for within-subject designs
Publication date: October 2018Source: Journal of Mathematical Psychology, Volume 86Author(s): Farouk S. Nathoo, Robyn E. Kilshaw, Michael E.J. MassonAbstractWe develop a Bayesian highest-density interval (HDI) for use in within-subject designs. This credible interval is based on a standard noninformative Jeffreys prior and a modified posterior distribution that conditions on both the data and point estimates of the subject-specific random effects. Conditioning on the estimated random effects removes between-subject variance and produces intervals that are the Bayesian analogue of the within-subject confidence interval prop...
Source: Journal of Mathematical Psychology - August 22, 2018 Category: Psychiatry & Psychology Source Type: research
Tree inference: Selective influence in multinomial processing trees with supplementary measures such as response time
Publication date: October 2018Source: Journal of Mathematical Psychology, Volume 86Author(s): Richard Schweickert, Xiaofang ZhengAbstractMultinomial Processing Trees are successful models of response probabilities for many phenomena. Empirical validation is often based on manipulating an experimental factor intended to selectively influence a process represented in a Multinomial Processing Tree, to see whether the factor indeed has an effect on and only on a parameter associated with that process. Response times are rarely included, but have great potential for increasing resolution. We consider Multinomial Processing Tree...
Source: Journal of Mathematical Psychology - August 21, 2018 Category: Psychiatry & Psychology Source Type: research
Ratios and differences in perceptual comparison: A reexamination of Torgerson’s conjecture
Publication date: August 2018Source: Journal of Mathematical Psychology, Volume 85Author(s): Randolph C. Grace, Nicola J. Morton, Matthew D. Ward, Anna J. Wilson, Simon KempAbstractHow do we compare stimuli that vary in magnitude? According to a well-known conjecture by Torgerson (1961), observers perceive only a single relation between stimuli, that is either a ratio or difference, but which one cannot be determined empirically. Previous research has used direct scaling procedures in which observers have judged ratios and differences numerically, but with mixed results. We used a novel behavioral task in which observers l...
Source: Journal of Mathematical Psychology - August 11, 2018 Category: Psychiatry & Psychology Source Type: research
Signed difference analysis: Testing for structure under monotonicity
We describe the theory of oriented matroids as it applies to SDA and derive tests for both linear and nonlinear models. In addition, we show that state-trace analysis is a special case of SDA which we extend to models such as additive conjoint measurement where each dependent variable is the same unspecified monotonic function of a linear combination of latent variables. Lastly, we show how measurement error can be accommodated based on the model-fitting approach developed by Kalish et al. (2016). (Source: Journal of Mathematical Psychology)
Source: Journal of Mathematical Psychology - August 3, 2018 Category: Psychiatry & Psychology Source Type: research
Studying associative learning without solving learning equations
Publication date: August 2018Source: Journal of Mathematical Psychology, Volume 85Author(s): Stefano GhirlandaAbstractI introduce a simple mathematical method to calculate the associative strengths of stimuli in many models of associative learning, without solving the models’ learning equations and without simulating the learning process. The method applies to many models, including the Rescorla and Wagner (1972) model, the replaced elements model of Brandon et al. (2000), and Pearce’s (1987) configural model. I illustrate the method by calculating the predictions of these three models in summation and blocking experim...
Source: Journal of Mathematical Psychology - August 2, 2018 Category: Psychiatry & Psychology Source Type: research
Editorial Board
Publication date: June 2018Source: Journal of Mathematical Psychology, Volume 84Author(s): (Source: Journal of Mathematical Psychology)
Source: Journal of Mathematical Psychology - July 10, 2018 Category: Psychiatry & Psychology Source Type: research
Parameter estimation of the Linear Phase Correction model by hierarchical linear models
Publication date: June 2018Source: Journal of Mathematical Psychology, Volume 84Author(s): Dominic Noy, Raquel MenezesAbstractThe control of human motor timing is captured by models that make assumptions about the underlying information processing mechanisms. A paradigm for its inquiry is the Sensorimotor Synchronization task, in which an individual is required to synchronize the movements of an effector, like the finger, with repetitive appearing onsets of an external event. The Linear Phase Correction model is a cognitive model that captures the asynchrony dynamics between the finger taps and the event onsets. However, w...
Source: Journal of Mathematical Psychology - July 10, 2018 Category: Psychiatry & Psychology Source Type: research
Approaching subjective interval timing with a non-Gaussian perspective
Publication date: June 2018Source: Journal of Mathematical Psychology, Volume 84Author(s): Tomás Gallo Aquino, Raphael Yokoingawa de Camargo, Marcelo Bussotti ReyesAbstractPerceiving time intervals is an essential ability of many animals, whose psychophysical properties have yet to be fully understood. A common theoretical approach is to consider that internal representations of time intervals are reflected in probability distribution functions. Depending on the mechanism proposed for interval timing inverse Gaussian and log-normal probability distributions are candidate distributions to represent internal representations...
Source: Journal of Mathematical Psychology - July 10, 2018 Category: Psychiatry & Psychology Source Type: research
A tutorial on joint models of neural and behavioral measures of cognition
Publication date: June 2018Source: Journal of Mathematical Psychology, Volume 84Author(s): James J. Palestro, Giwon Bahg, Per B. Sederberg, Zhong-Lin Lu, Mark Steyvers, Brandon M. TurnerAbstractA growing synergy between the fields of cognitive neuroscience and mathematical psychology has sparked the development of several unique statistical approaches exploiting the benefits of both disciplines (Turner, Forstmann et al., 2017). One approach in particular, called joint modeling, attempts to model the covariation between the parameters of “submodels” intended to capture important patterns in each stream of data. Joint m...
Source: Journal of Mathematical Psychology - July 10, 2018 Category: Psychiatry & Psychology Source Type: research
Quantum like modeling of decision making: Quantifying uncertainty with the aid of Heisenberg–Robertson inequality
Publication date: June 2018Source: Journal of Mathematical Psychology, Volume 84Author(s): Fabio Bagarello, Irina Basieva, Emmanuel M. Pothos, Andrei KhrennikovAbstractThis paper contributes to quantum-like modeling of decision making (DM) under uncertainty through application of Heisenberg’s uncertainty principle (in the form of the Robertson inequality). In this paper we apply this instrument to quantify uncertainty in DM performed by quantum-like agents. As an example, we apply the Heisenberg uncertainty principle to the determination of mutual interrelation of uncertainties for “incompatible questions” used to be...
Source: Journal of Mathematical Psychology - July 10, 2018 Category: Psychiatry & Psychology Source Type: research
