A hierarchical bayesian statistical framework for response time distributions

This paper provides a statistical framework for estimating higher-order characteristics of the response time distribution, such as the scale (variability) and shape. Consideration of these higher order characteristics often provides for more rigorous theory development in cognitive and perceptual psychology (e.g., Luce, 1986). RT distribution for a single participant depends on certain participant characteristics, which in turn can be thought of as arising from a distribution of latent variables. The present work focuses on the three-parameter Weibull distribution, with parameters for shape, scale, and shift (initial value). Bayesian estimation in a hierarchical framework is conceptually straightforward. Parameter estimates, both for participant quantities and population parameters, are obtained through Markov Chain Monte Carlo methods. The methods are illustrated with an application to response time data in an absolute identification task. The behavior of the Bayes estimates are compared to maximum likelihood (ML) estimates through Monte Carlo simulations. For small sample size, there is an occasional tendency for the ML estimates to be unreasonably extreme. In contrast, by borrowing strength across participants, Bayes estimation shrinks extreme estimates. The results are that the Bayes estimators are more accurate than the corresponding ML estimators.We are grateful to Michael Stadler who allowed us use of his data. This research is supported by (a) National Science Foundation Grant SES-0095919 to J. Rouder, D. Sun, and P. Speckman, (b) University of Missouri Research Board Grant 00-77 to J. Rouder, (c) National Science Foundation grant DMS-9972598 to Sun and Speckman, and (d) a grant from the Missouri Department of Conservation to D. Sun.     

Spatial attention: different mechanisms for central and peripheral temporal precues?

The external noise paradigm (Z.-L. Lu & B. A. Dosher, 1998) was applied to investigate mechanisms of spatial attention in location precuing. Observers were precued or simultaneously cued to identify 1 of 4 pseudocharacters embedded in various amounts of external noise. The cues were either central or peripheral. Both central and peripheral precuing significantly reduced threshold in the presence of high external noise (16% and 17.5%). Only peripheral precuing significantly reduced threshold in the presence of low, or no, external noise (11%). A perceptual template model identified different mechanisms of attention for central and peripheral precuing, external noise exclusion for central precuing, and a combination of external noise exclusion and stimulus enhancement (or equivalently, internal additive noise reduction) for peripheral cuing.     

Cultural values,system justification,meritocratic beliefs,and evaluations of governments' performance in handling the COVID-19 crisis

System justification and meritocratic beliefs legitimize the status quo of economic, social, and political arrangements, and may correlate with favourable evaluations of governments' performance during the COVID-19 pandemic. This study furthers research on this topic by examining (1) the cultural value antecedents of system justification and meritocratic beliefs, and (2) the differential effects of these on attitudes toward ingroups and outgroups from an intergroup perspective. The results show that collectivist values positively predict system justification and meritocratic beliefs, whereas a similar effect was not observed for individualist values. As hypothesized, system justification motivation was positively associated with favourable evaluation of the Chinese government (an ingroup). By contrast, system justification and meritocratic beliefs were negatively associated with evaluation of the American government (an outgroup). We discussed the implications for understandings of the cultural value bases of system justification and meritocratic beliefs, and the relevance of the lens of intergroup relations in studying those beliefs.     

COVID-19 non-death loss and acceptance coping: A 3-wave cross-lagged panel analysis

Numerous individuals have lost loved ones during the COVID-19 pandemic while millions of others have also experienced ongoing pervasive non-death loss. The understanding of how people deal with non-death loss is still relatively limited. Incorporating theory of coping and loss, this study examines the reciprocal relationship between non-death loss and acceptance coping. Based on the results of a cross-lagged panel model involving 314 participants in China, we found that before the end of the zero-Covid policy, non-death loss at Time 1 predicted less acceptance coping at Time 2, but in the opening up stage in late 2022, non-death loss at time 2 did not predict acceptance coping at time 3. The findings have significant implications for understanding the interplay between non-death loss and acceptance coping and highlights abrupt psychological changes during the COVID-19 pandemic.     

教学心理学情感维度上的一种教材处理策略——心理匹配

在教学心理学领域中,人们往往习惯于从认知维度探索教材的优化处理策略,缺乏情感维度上的相应研究。奥苏贝尔虽提出意义学习的两个内在先决条件：一是学习者有同化新材料的认知结构;二是学习者有意义学习的心向．但他本人也仅从影响学生认知结构的角度,提出教材的认知处理策略──先行组织者策略．而未从影响学生心向的角度．提出教材的情感处理策略。鉴此,本文从情感维度上提出教材处理的心理匹配策略．以冀与认知策略一起共同优化处理教材、呈现教学内容环节,并阐明心理匹配策略的内涵、机制、作用和种类。     

A Bayesian Theory of Sequential Causal Learning and Abstract Transfer

Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause‐effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre‐training (or even post‐training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue‐outcome co‐occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge.     

不同年龄城乡青少年价值取向的多方法复合式分析

本研究采用多方法、多特征的新思路,以4种测量方法分析不同亚文化背景下424名青少年的集体──个体价值取向（collectivism－individualismvalueorientation）的特点及其发展变化趋势,试图在价值取向的理论构思和研究方法论两方面作新的探索。结果表明：（1）不同年龄段、不同地区的被试,其集体──个体价值取向存在着显著差异;（2）4种测量方法之间结果的相关非常显著,多方法复合式分析具有聚合效度;（3）在集体──个体价值取向方向上,我国被试更倾向集体。本研究在方法学上和交叉文化差异研究中都有其积极意义,为进一步研究提供了依据。     

3—7岁儿童理解类包含概念的初步研究——对皮亚杰类包含实验的初步意见

皮亚杰认为对类包含关系的理解,是判断儿童思惟是否达到守恒的一个标志。他认为学前儿童不能理解类包含概念,我们拟通过实验措施,观察启发教育对幼儿掌握类包含关系的作用。 我们还认为皮亚杰的类包含实验容易使儿童从数量上考虑,没有强调类与子类在性质上的从属关系,为此,我们另外设计了类包含实验及分类实验,以资和皮亚杰的结果作比较。