Equivalence testing, also called negligible effect significance testing (NEST), is appropriate when a researcher would like to find evidence of a negligible association. However, since equivalence testing/NEST procedures are newer and considerably less popular than traditional difference-based null hypothesis significance testing, it is useful to give a gentle introduction to these methods. Accordingly, this tutorial article aims to provide an overview of NEST/equivalence testing procedures by describing the nature of the procedures, explaining when they should be used, defining what considerations should go into their application (including selecting a minimally meaningful effect size), and outlining how they may be conducted and interpreted. The tutorial article also includes examples and code in open-source software to illustrate how these procedures may be applied to real data. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
{"title":"A primer on equivalence (negligible effect) testing.","authors":"Nataly Beribisky, Robert A Cribbie","doi":"10.1037/met0000800","DOIUrl":"https://doi.org/10.1037/met0000800","url":null,"abstract":"<p><p>Equivalence testing, also called negligible effect significance testing (NEST), is appropriate when a researcher would like to find evidence of a negligible association. However, since equivalence testing/NEST procedures are newer and considerably less popular than traditional difference-based null hypothesis significance testing, it is useful to give a gentle introduction to these methods. Accordingly, this tutorial article aims to provide an overview of NEST/equivalence testing procedures by describing the nature of the procedures, explaining when they should be used, defining what considerations should go into their application (including selecting a minimally meaningful effect size), and outlining how they may be conducted and interpreted. The tutorial article also includes examples and code in open-source software to illustrate how these procedures may be applied to real data. (PsycInfo Database Record (c) 2026 APA, all rights reserved).</p>","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":" ","pages":""},"PeriodicalIF":7.8,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146143473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Planned missingness to reduce survey length: A sheep in wolf’s clothing.","authors":"Charlene Zhang, Paul R. Sackett, Saron Demeke","doi":"10.1037/met0000793","DOIUrl":"https://doi.org/10.1037/met0000793","url":null,"abstract":"","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":"24 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146122211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jay Verkuilen, Sydne T. McCluskey, Magdalen Beiting-Parrish, Aleksandra Kazakova, Howard T. Everson
{"title":"Using latent class analysis to justify a latent continuum in item development.","authors":"Jay Verkuilen, Sydne T. McCluskey, Magdalen Beiting-Parrish, Aleksandra Kazakova, Howard T. Everson","doi":"10.1037/met0000757","DOIUrl":"https://doi.org/10.1037/met0000757","url":null,"abstract":"","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":"28 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146122210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Supplemental Material for Using Latent Class Analysis to Justify a Latent Continuum in Item Development","authors":"","doi":"10.1037/met0000757.supp","DOIUrl":"https://doi.org/10.1037/met0000757.supp","url":null,"abstract":"","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":"5 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146101617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Supplemental Material for Planned Missingness to Reduce Survey Length: A Sheep in Wolf’s Clothing","authors":"","doi":"10.1037/met0000793.supp","DOIUrl":"https://doi.org/10.1037/met0000793.supp","url":null,"abstract":"","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":"16 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146101618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contaminant observations often cause problems when estimating the parameters of cognitive models. In this study, we tested and improved the robustness of parameter estimation using amortized Bayesian inference. We conducted systematic analyses in two settings: a toy example (i.e., a normal distribution with an unknown mean) and a popular cognitive model, the drift diffusion model. First, we studied the stylized sensitivity curve and the breakdown point of the estimators. Next, we proposed a simple data augmentation approach that incorporated a contamination distribution into the data-generating process during training to train robust estimators. We examined several robust estimators with different contamination distributions, and evaluated their performance and cost in terms of accuracy and efficiency loss relative to a standard estimator. Introducing contaminants from a Cauchy distribution during training significantly increases the robustness of the neural density estimator, as measured by bounded sensitivity functions and a substantially higher breakdown point. Overall, the proposed method is straightforward and practical to implement, with broad applicability in fields where outlier detection or removal is challenging. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
{"title":"Testing and improving the robustness of amortized bayesian inference for cognitive models.","authors":"Yufei Wu, Stefan T Radev, Francis Tuerlinckx","doi":"10.1037/met0000814","DOIUrl":"10.1037/met0000814","url":null,"abstract":"<p><p>Contaminant observations often cause problems when estimating the parameters of cognitive models. In this study, we tested and improved the robustness of parameter estimation using amortized Bayesian inference. We conducted systematic analyses in two settings: a toy example (i.e., a normal distribution with an unknown mean) and a popular cognitive model, the drift diffusion model. First, we studied the stylized sensitivity curve and the breakdown point of the estimators. Next, we proposed a simple data augmentation approach that incorporated a contamination distribution into the data-generating process during training to train robust estimators. We examined several robust estimators with different contamination distributions, and evaluated their performance and cost in terms of accuracy and efficiency loss relative to a standard estimator. Introducing contaminants from a Cauchy distribution during training significantly increases the robustness of the neural density estimator, as measured by bounded sensitivity functions and a substantially higher breakdown point. Overall, the proposed method is straightforward and practical to implement, with broad applicability in fields where outlier detection or removal is challenging. (PsycInfo Database Record (c) 2026 APA, all rights reserved).</p>","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":" ","pages":""},"PeriodicalIF":7.8,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146053387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Simplicity, complexity, and the standardized mean difference between two independent groups.","authors":"Paul Dudgeon","doi":"10.1037/met0000780","DOIUrl":"https://doi.org/10.1037/met0000780","url":null,"abstract":"","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":"1 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145703935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Psychological theories are often expressed verbally using natural language, which may lead to varying interpretations of the phenomenon under study. This potential confusion can be mitigated by formalizing verbal theories using mathematical language, which can help in defining, analyzing, and interpreting one's hypotheses in quantitative terms. Differential equations (DEs) are a class of models in the dynamical systems framework, particularly suited to many dynamic theories in psychology. However, there is a lack of tools for translating verbal theories into DE systems. To facilitate this translation, we introduce SimDE (https://simde.ucdavis.edu/), an open-access R Shiny application that allows users to specify a DE model and then simulate the trajectories of each variable over time. SimDE provides an interface to simulate a range of DE models, with features such as: (a) first- or second-order DEs (e.g., exponential, oscillatory), (b) models with or without a dynamic error term (ordinary or stochastic DEs), (c) models with coupling dynamics. Users have the flexibility of plotting these systems in order to see the pattern of changes over time and determine the appropriateness of the model for the phenomenon they are trying to study. The goal of our app is to serve as a tool for researchers who want to explore DE models for their psychological theories before they even collect data. It can also help researchers to study the implicit assumptions of their systems defined with such DEs and further refine them as needed. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
心理学理论通常是用自然语言口头表达的，这可能会导致对所研究现象的不同解释。这种潜在的困惑可以通过使用数学语言形式化口头理论来减轻，这有助于用定量术语定义、分析和解释一个人的假设。微分方程（DEs）是动力系统框架中的一类模型，特别适用于心理学中的许多动力学理论。然而，缺乏将语言理论转换为DE系统的工具。为了方便这种转换，我们介绍了SimDE (https://simde.ucdavis.edu/)，这是一个开放访问的R Shiny应用程序，允许用户指定DE模型，然后模拟每个变量随时间的轨迹。SimDE提供了一个界面来模拟一系列DE模型，其特征包括：(a)一阶或二阶DE（例如，指数，振荡），(b)有或没有动态误差项的模型（普通或随机DE）， (c)具有耦合动力学的模型。用户可以灵活地绘制这些系统，以便看到随时间变化的模式，并确定模型是否适合他们试图研究的现象。我们的应用程序的目标是为那些想要在收集数据之前为他们的心理学理论探索DE模型的研究人员提供工具。它还可以帮助研究人员研究用这些de定义的系统的隐含假设，并根据需要进一步完善它们。（PsycInfo Database Record (c) 2025 APA，版权所有）。
{"title":"SimDE App: Simulating and visualizing formal theories using differential equations.","authors":"Rohit Batra,Emorie D Beck,Meng Chen,Emilio Ferrer","doi":"10.1037/met0000807","DOIUrl":"https://doi.org/10.1037/met0000807","url":null,"abstract":"Psychological theories are often expressed verbally using natural language, which may lead to varying interpretations of the phenomenon under study. This potential confusion can be mitigated by formalizing verbal theories using mathematical language, which can help in defining, analyzing, and interpreting one's hypotheses in quantitative terms. Differential equations (DEs) are a class of models in the dynamical systems framework, particularly suited to many dynamic theories in psychology. However, there is a lack of tools for translating verbal theories into DE systems. To facilitate this translation, we introduce SimDE (https://simde.ucdavis.edu/), an open-access R Shiny application that allows users to specify a DE model and then simulate the trajectories of each variable over time. SimDE provides an interface to simulate a range of DE models, with features such as: (a) first- or second-order DEs (e.g., exponential, oscillatory), (b) models with or without a dynamic error term (ordinary or stochastic DEs), (c) models with coupling dynamics. Users have the flexibility of plotting these systems in order to see the pattern of changes over time and determine the appropriateness of the model for the phenomenon they are trying to study. The goal of our app is to serve as a tool for researchers who want to explore DE models for their psychological theories before they even collect data. It can also help researchers to study the implicit assumptions of their systems defined with such DEs and further refine them as needed. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":"35 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145673915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yinon Nachshon,Haim Cohen,Paz M Naim,Emil Saucan,Anat Maril
This study investigates the dynamics of semantic associations by exploring the interplay between continuity and direction in a geometric semantic space. While acknowledging the role of continuity in guiding associations, our work introduces Direction as a crucial factor influencing transitions. Conceptually, we define the stream of associations as movement along a sequence of objects, with attention amplifying dissimilarity and progressing in the direction of maximal resolution, conceptualized as the most "stretched" direction. The core of our methodological innovation lies in the introduction of a unique adaptation of discrete Ricci curvature to measure the direction of maximal resolution, tailored specifically to a hypergraph framework. By reinterpreting traditional curvature concepts within this context, we provide a novel quantitative approach to understanding semantic transitions. Empirically, our investigation involves a categorical fluency task where participants name animals, allowing us to construct a hypergraph for transition analysis. We evaluate two hypotheses: the relationship between edge "stretchiness" and transition probability, and the enhanced explanatory power of considering Similarity + Direction over similarity alone. Our model challenges the standard view by proposing that the stream of thought moves in the direction of maximal resolution. By introducing the concept of Ricci curvature in a hypernetwork, we offer a novel tool for quantifying resolution and demonstrate its practical application in the context of semantic space. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
本研究通过探索几何语义空间中连续性和方向性之间的相互作用来研究语义关联的动态。在承认连续性在指导协会中的作用的同时，我们的工作引入了方向作为影响过渡的关键因素。从概念上讲，我们将联想流定义为沿着一系列对象的运动，注意放大差异，并朝着最大分辨率的方向前进，概念化为最“拉伸”的方向。我们方法创新的核心在于引入了一种独特的离散里奇曲率来测量最大分辨率的方向，专门为超图框架量身定制。通过在这种情况下重新解释传统的曲率概念，我们提供了一种新的定量方法来理解语义转换。根据经验，我们的调查涉及到一个分类流畅性任务，参与者命名动物，允许我们构建一个超图进行过渡分析。我们评估了两个假设：边缘“拉伸”与转移概率之间的关系，以及考虑相似性+方向比单独考虑相似性更强的解释力。我们的模型通过提出思想流在最大分辨率的方向上运动来挑战标准观点。通过在超网络中引入Ricci曲率的概念，我们提供了一种量化分辨率的新工具，并展示了其在语义空间中的实际应用。（PsycInfo Database Record (c) 2025 APA，版权所有）。
{"title":"Ricci curvature and the stream of thought.","authors":"Yinon Nachshon,Haim Cohen,Paz M Naim,Emil Saucan,Anat Maril","doi":"10.1037/met0000809","DOIUrl":"https://doi.org/10.1037/met0000809","url":null,"abstract":"This study investigates the dynamics of semantic associations by exploring the interplay between continuity and direction in a geometric semantic space. While acknowledging the role of continuity in guiding associations, our work introduces Direction as a crucial factor influencing transitions. Conceptually, we define the stream of associations as movement along a sequence of objects, with attention amplifying dissimilarity and progressing in the direction of maximal resolution, conceptualized as the most \"stretched\" direction. The core of our methodological innovation lies in the introduction of a unique adaptation of discrete Ricci curvature to measure the direction of maximal resolution, tailored specifically to a hypergraph framework. By reinterpreting traditional curvature concepts within this context, we provide a novel quantitative approach to understanding semantic transitions. Empirically, our investigation involves a categorical fluency task where participants name animals, allowing us to construct a hypergraph for transition analysis. We evaluate two hypotheses: the relationship between edge \"stretchiness\" and transition probability, and the enhanced explanatory power of considering Similarity + Direction over similarity alone. Our model challenges the standard view by proposing that the stream of thought moves in the direction of maximal resolution. By introducing the concept of Ricci curvature in a hypernetwork, we offer a novel tool for quantifying resolution and demonstrate its practical application in the context of semantic space. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":"61 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145673916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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