Journal of Mathematical Psychology最新文献

Systems factorial technology: Unconditional interaction contrasts for correct and incorrect responses 系统析因技术：正确和错误反应的无条件交互对比

IF 1.5 4区心理学

Journal of Mathematical Psychology Pub Date : 2026-05-01 Epub Date: 2026-04-28 DOI: 10.1016/j.jmp.2026.102983

Matthias Gondan, Lukas Legner

{"title":"Systems factorial technology: Unconditional interaction contrasts for correct and incorrect responses","authors":"Matthias Gondan, Lukas Legner","doi":"10.1016/j.jmp.2026.102983","DOIUrl":"10.1016/j.jmp.2026.102983","url":null,"abstract":"<div><div>Response time is probably the most important metric in cognitive psychology. Many studies focus on average response time, but even more information can be obtained considering the shape of the response time distributions. In their seminal work, Townsend and Nozawa (1995) investigated the interaction contrast of response time distributions in two-factorial experiments for different cognitive architectures, including serial and parallel processing, with exhaustive and self-terminating stopping rules. They derived distinct, nonparametric predictions for the interaction contrast under fairly weak assumptions: selective influence of the factorial manipulations, and stochastic ordering of the processing times for the different factor levels. Their original theory is limited to tasks with ceiling accuracy. Extensions to more difficult tasks either conditioned the response time distributions on accuracy, which interferes with the assumption of stochastic ordering. Other approaches focused on a special case of the paradigm (i.e., redundant signals tasks). Here we show that with a slight extension of the stochastic dominance assumption, Townsend and Nozawa’s theorems can be generalized to difficult tasks that entail non-negligible error rates. We demonstrate statistical tests and illustrate methods to assess their power. We investigate additional generalizations of the theory to higher-order experimental manipulations and larger networks of serial and parallel processes. Interesting special cases such as redundant signals tasks and parametric experimental variations, as well as applications of the theory in areas outside cognitive psychology are proposed and discussed. More than 150 years after Donders, we can finally design and analyze interesting reaction time experiments with non-negligible error rates.</div></div>","PeriodicalId":50140,"journal":{"name":"Journal of Mathematical Psychology","volume":"129 ","pages":"Article 102983"},"PeriodicalIF":1.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147798360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sampling in constrained space: Efficient estimation of model evidence under equality and inequality constraints 约束空间中的抽样：等式和不等式约束下模型证据的有效估计

IF 1.5 4区心理学

Journal of Mathematical Psychology Pub Date : 2026-05-01 Epub Date: 2026-04-28 DOI: 10.1016/j.jmp.2026.102989

Lukas L. Lengersdorff , Maarten Marsman

{"title":"Sampling in constrained space: Efficient estimation of model evidence under equality and inequality constraints","authors":"Lukas L. Lengersdorff , Maarten Marsman","doi":"10.1016/j.jmp.2026.102989","DOIUrl":"10.1016/j.jmp.2026.102989","url":null,"abstract":"<div><div>Many scientific theories imply equality and inequality constraints on the statistical model underlying the observed data. Incorporating such constraints into hypothesis testing increases the efficiency and precision of inference. However, existing tools of testing such hypotheses are computationally expensive and do not scale well to complex sets of constraints. Here, we introduce Sampling in Constrained Space (SICS), a general approach for performing Bayesian hypothesis testing on constrained models. Combining Hamiltonian Monte Carlo algorithms with reparameterization, SICS allows the efficient sampling of the posterior distribution from those sections of the parameter space that fulfill all constraints. This, in turn, enables estimating the marginal likelihood under the constrained model, through established algorithms such as bridge sampling. We demonstrate the versatility of SICS by analyzing a learning task dataset using constrained reinforcement learning models, from both a single-level and hierarchical perspective. Our results show that SICS outperforms previous approaches in terms of precision and efficiency. By providing guidelines on its application, we hope to make SICS an integral part of scientists’ inferential toolkit.</div></div>","PeriodicalId":50140,"journal":{"name":"Journal of Mathematical Psychology","volume":"129 ","pages":"Article 102989"},"PeriodicalIF":1.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147798361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Representing choice probabilities by ranking probabilities via entropy maximization 通过熵最大化排序概率来表示选择概率

IF 1.5 4区心理学

Journal of Mathematical Psychology Pub Date : 2026-03-01 Epub Date: 2026-01-27 DOI: 10.1016/j.jmp.2026.102970

Karim Kilani , Hans Colonius

引用次数: 0

Analytical bifurcation analysis of mean-field Ising models reveals connectivity as a risk factor for psychopathology 平均场Ising模型的分析分岔分析揭示了连通性是精神病理的一个危险因素

IF 1.5 4区心理学

Journal of Mathematical Psychology Pub Date : 2026-03-01 Epub Date: 2025-12-18 DOI: 10.1016/j.jmp.2025.102968

Han L.J. van der Maas, Lourens Waldorp

引用次数: 0

Identifiability of the polytomous local independence model with graded knowledge structures 具有分级知识结构的多自治局部独立模型的可识别性

IF 1.5 4区心理学

Journal of Mathematical Psychology Pub Date : 2026-03-01 Epub Date: 2025-12-04 DOI: 10.1016/j.jmp.2025.102956

Luca Stefanutti , Andrea Spoto

{"title":"Identifiability of the polytomous local independence model with graded knowledge structures","authors":"Luca Stefanutti , Andrea Spoto","doi":"10.1016/j.jmp.2025.102956","DOIUrl":"10.1016/j.jmp.2025.102956","url":null,"abstract":"<div><div>This article provides initial theoretical results concerning the identifiability of the polytomous local independence model (PoLIM), which is an extension of the basic local independence model (BLIM) to polytomous knowledge structures. It is well-known that the BLIM is not identifiable for graded knowledge structures. This is because there exist parameter transformations, named outcome preserving transformations, that leave unchanged the outcome of the prediction function of the model. In this article a twofold generalization is carried out. On the one side, we extend the notion of gradedness to polytomous structures, and, on the other side, we generalize the outcome preserving transformations to the case of polytomous items. These generalizations lead to the conclusion that the PoLIM is not identifiable for graded polytomous structures. This result generalizes a well-known one with the dichotomous structures. The role of equally informative items in the identifiability of the PoLIM is also investigated. The formal results are accompanied by a numerical example that applies those results to the PoLIM with a concrete polytomous structure that turns out to be graded.</div></div>","PeriodicalId":50140,"journal":{"name":"Journal of Mathematical Psychology","volume":"128 ","pages":"Article 102956"},"PeriodicalIF":1.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Associative updates for temporal contingencies 时间偶然性的关联更新

IF 1.5 4区心理学

Journal of Mathematical Psychology Pub Date : 2026-03-01 Epub Date: 2026-01-31 DOI: 10.1016/j.jmp.2026.102971

Niels J. Verosky

引用次数: 0

Information of absence: Capacity measures for parallel AND processing 缺席信息：并行和处理的容量度量

IF 1.5 4区心理学

Journal of Mathematical Psychology Pub Date : 2026-03-01 Epub Date: 2025-12-22 DOI: 10.1016/j.jmp.2025.102967

Nicholas A. Altieri

{"title":"Information of absence: Capacity measures for parallel AND processing","authors":"Nicholas A. Altieri","doi":"10.1016/j.jmp.2025.102967","DOIUrl":"10.1016/j.jmp.2025.102967","url":null,"abstract":"<div><div>Howard and colleagues (2021) reported evidence that significant resources are used to process target-absent information in detection designs. This has major implications for measuring a system’s “capacity”, particularly when using AND decision rules. Chief among these concerns are the inflated capacity measurements commonly reported in the literature. To address this, the authors suggested using a full-factorial identification decision rule instead of simple detection. Here, a new capacity measure is calculated by comparing response times in single-target trials to those obtained from double and target-absent trials. Besides fundamentally altering the design, I argue this newly proposed coefficient may deflate capacity when target-absent responses are systematically slow relative to true parallel independent predictions, or under certain violations of context-invariance. I instead propose comparing responses in the double-target AND condition to parallel independent minimum time predictions derived from single-target “no” trials. This should avoid spurious findings of super or overly limited capacity and thus provide capacity estimates more closely resembling OR detection.</div></div>","PeriodicalId":50140,"journal":{"name":"Journal of Mathematical Psychology","volume":"128 ","pages":"Article 102967"},"PeriodicalIF":1.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A hitchhiker’s guide to information theoretical measures in psychology 心理学中信息理论测量的搭便车指南

IF 1.5 4区心理学

Journal of Mathematical Psychology Pub Date : 2026-03-01 Epub Date: 2026-01-06 DOI: 10.1016/j.jmp.2025.102969

Niels van Santen, Yves Rosseel, Daniele Marinazzo

引用次数: 0

Causal analysis of absolute and relative risk reductions 绝对和相对风险降低的原因分析

IF 1.5 4区心理学

Journal of Mathematical Psychology Pub Date : 2025-12-01 Epub Date: 2025-09-03 DOI: 10.1016/j.jmp.2025.102942

Björn Meder , Charley M. Wu , Felix G. Rebitschek

{"title":"Causal analysis of absolute and relative risk reductions","authors":"Björn Meder , Charley M. Wu , Felix G. Rebitschek","doi":"10.1016/j.jmp.2025.102942","DOIUrl":"10.1016/j.jmp.2025.102942","url":null,"abstract":"<div><div>Any medical innovation must first prove its benefits with reliable evidence from clinical trials. Evidence is commonly expressed using two metrics, summarizing treatment benefits based on either absolute risk reductions (ARRs) or relative risk reductions (RRRs). Both metrics are derived from the same data, but they implement conceptually distinct ideas. Here, we analyze these risk reductions measures from a causal modeling perspective. First, we show that ARR is equivalent to <span><math><mrow><mi>Δ</mi><mi>P</mi></mrow></math></span>, while RRR is equivalent to causal power, thus clarifying the implicit causal assumptions. Second, we show how this formal equivalence establishes a relationship with causal Bayes nets theory, offering a basis for incorporating risk reduction metrics into a computational modeling framework. Leveraging these analyses, we demonstrate that under dynamically varying baseline risks, ARRs and RRRs lead to strongly diverging predictions. Specifically, the inherent assumption of a linear parameterization of the underlying causal graph can lead to incorrect conclusions when generalizing treatment benefits (e.g, predicting the effect of a vaccine in new populations with different baseline risks). Our analyses highlight the shared principles underlying risk reduction metrics and measures of causal strength, emphasizing the potential for explicating causal structure and inference in medical research.</div></div>","PeriodicalId":50140,"journal":{"name":"Journal of Mathematical Psychology","volume":"127 ","pages":"Article 102942"},"PeriodicalIF":1.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling meta-reasoning processes using diffusion and quantum random walk models 使用扩散和量子随机游走模型建模元推理过程

IF 1.5 4区心理学

Journal of Mathematical Psychology Pub Date : 2025-12-01 Epub Date: 2025-11-05 DOI: 10.1016/j.jmp.2025.102952

Ritesh K. Malaiya, Richard M. Golden

{"title":"Modeling meta-reasoning processes using diffusion and quantum random walk models","authors":"Ritesh K. Malaiya, Richard M. Golden","doi":"10.1016/j.jmp.2025.102952","DOIUrl":"10.1016/j.jmp.2025.102952","url":null,"abstract":"<div><div>Meta-reasoning studies investigate the role of metacognitive processes in <em>monitoring</em> the success likelihood of an ongoing Reasoning task expected to require Longer Deliberation Time (RLDT), and accordingly, <em>control</em> further cognitive resource allocation to maximize success likelihood. A Meta-reasoning study may require participants to report their intermediate confidence judgment repeatedly within RLDT, e.g., a response that <em>I am 70% confident that the problem is solvable</em>, requested every 15 s. Based on existing Meta-reasoning studies, the current study first identified a set of observable Meta-reasoning phenomena on how intermediate confidence judgment evolves within RLDT and its impact on response choice and response time. Then, based on identified Meta-reasoning phenomena, certain computational features, serving as guidelines, were proposed to facilitate the construction and evaluation of random walk models describing these phenomena. The Markov Random-Walk formulation of the Drift-Diffusion Model (MR-DDM) and the Quantum Random-Walk Model (QRM) have been widely utilized to model response choice, response time, and intermediate and final confidence judgments in decision-making studies. Hence, the proposed computational features were utilized to evaluate the effectiveness of existing MR-DDM and QRM in describing meta-reasoning processes. Also, potential extensions of MR-DDM and QRM were identified for further empirical investigations. The current study also briefly reviewed an existing Item Response Theory (IRT) based extension of a continuous state continuous time Drift-Diffusion Model, named Q-Diffusion, that has been utilized to model RLDT without explicitly constraining the model to describe Meta-reasoning phenomena. Utilizing insights from Q-Diffusion and proposed computational features, the current study identified potential extensions of the MR-DDM for further empirical investigations.</div></div>","PeriodicalId":50140,"journal":{"name":"Journal of Mathematical Psychology","volume":"127 ","pages":"Article 102952"},"PeriodicalIF":1.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0