The darker side of accommodating others: Examining the interpersonal structure of maladaptive constructs

To better understand the greater prevalence of depression among women, compared to men, we explored the darker side of accommodating others by examining where maladaptive relational constructs fit within a general structural framework provided by the interpersonal circumplex and 5-factor model of personality. Participants were four samples of undergraduate students (Ns = 302–2070) who completed questionnaires. Results indicated two clusters of maladaptive items: Submission with Connection and Submission without Connection. In general, the most maladaptive relational constructs were concentrated in the first cluster and were located in the low agency, low communion region of the interpersonal circumplex.     

条件推理的条件概率模型述评

该文从理论模型和实验范式两个方面对Oaksford等人提出的条件推理概率模型作了综合评述,并充分肯定该模型将演绎推理与归纳推理结合起来进行研究对推理心理学的发展所作出的重要贡献。     

日常经验研究：一种独具特色的研究方法

日常经验研究是一种通过研究日常生活中各种事件发生时人们的瞬时感受而在自发、自然的情景中对人的心理现象、过程进行探索的方法。其目的是通过获得关于个人日常生活中某些特定事件或特定时刻的详细描述,来提取有关思维、情绪、行为的持久性、周期性、变化以及时间结构等方面的信息,并确定上述因素之间的情境性以及倾向性相关。日常经验研究的价值和意义在于在方法论三角互证原则的指导下,与其他各种方法结合起来,帮助研究者从不同角度理解心理现象及其过程,从而达到最大限度地探索、了解人类心理世界的目的     

条件推理中的二元效应初探

通过预备实验选取前件(或后件)是二元(或多元)的5种条件命题的4种推理形式作为实验材料,以大学本科生为被试,考察了五种不同条件命题类型对4种推理结果的影响.结果表明命题类型、推理规则以及两者的交互作用都非常显著.这个结果进一步验证了条件推理的集合映射模型.     

态度改变：说服策略研究的回顾与展望

态度是社会心理学研究的重要领域,近年来研究者发现通过说服可以改变个体的态度,所以态度的说服策略成为一个研究的重点。说服包括了陈述论据和事实,推理,做结论和说明所推荐行为方式的积极效果,所有的一切都是为了使受众相信并且按照这种行为方式行事。本文沿着历史的脉络,从不同的角度阐述了各种说服策略的理论解释及其实验研究,并在此基础上叙述了说服策略未来研究趋势。     

A computational model of spatial visualization capacity

Visualizing spatial material is a cornerstone of human problem solving, but human visualization capacity is sharply limited. To investigate the sources of this limit, we developed a new task to measure visualization accuracy for verbally-described spatial paths (similar to street directions), and implemented a computational process model to perform it. In this model, developed within the Adaptive Control of Thought-Rational (ACT-R) architecture, visualization capacity is limited by three mechanisms. Two of these (associative interference and decay) are longstanding characteristics of ACT-R’s declarative memory. A third (spatial interference) is a new mechanism motivated by spatial proximity effects in our data. We tested the model in two experiments, one with parameter-value fitting, and a replication without further fitting. Correspondence between model and data was close in both experiments, suggesting that the model may be useful for understanding why visualizing new, complex spatial material is so difficult.     

Using relational structure to detect symmetry: a Voronoi tessellation based model of symmetry perception

Numerous models of symmetry perception have been proposed in recent years. Unfortunately, it is difficult to assess the relative utility of these models as little effort has been made to directly compare them. This paper outlines a new model of symmetry perception based upon the relational structure revealed by Voronoi tessellation. The model has been developed in response to evidence suggesting that the human visual system is generating a Voronoi-like representation at an early stage in processing. Bayesian model selection is employed to compare the performance of the Voronoi model to that of five previously published models across six empirical datasets. The results indicate that the Voronoi model provides a more likely account of the data than the five alternative models.     

Test of a Level of Aspiration model of group decision making: Non-obvious group preference reversal due to an irrelevant alternative

We conducted two experiments that investigated a non-obvious prediction of a Level of Aspiration (LOA) model of group decision making. In both experiments, groups chose among three alternatives, A, B, and C, with C always being least preferred by all of the group members. In each experiment, by manipulating the nature of alternative C, we created two conditions differing in whether only A or only B was acceptable to all members. In support of the LOA model, groups tended to choose the alternative acceptable to all members, even when (Experiment 2) a majority of members most preferred a different alternative. Implications of the results for the LOA model are discussed in the context of social choice theory.     

Measurement by subjective estimation: Testing for separable representations

Studying how individuals compare two given quantitative stimuli, say d₁ and d₂, is a fundamental problem. One very common way to address it is through ratio estimation, that is to ask individuals not to give values to d₁ and d₂, but rather to give their estimates of the ratio p=d₁/d₂. Several psychophysical theories (the best known being Stevens’ power-law) claim that this ratio cannot be known directly and that there are cognitive distortions on the apprehension of the different quantities. These theories result in the so-called separable representations [Luce, R. D. (2002). A psychophysical theory of intensity proportions, joint presentations, and matches. Psychological Review, 109, 520–532; Narens, L. (1996). A theory of ratio magnitude estimation. Journal of Mathematical Psychology, 40, 109–788], which include Stevens’ model as a special case. In this paper we propose a general statistical framework that allows for testing in a rigorous way whether the separable representation theory is grounded or not. We conclude in favor of it, but reject Stevens’ model. As a byproduct, we provide estimates of the psychophysical functions of interest.     

A fast numerical algorithm for the estimation of diffusion model parameters

In this paper, we describe a new algorithmic approach for parameter estimation in Ratcliff's [(1978). A theory of memory retrieval. Psychological Review, 85 (2), 59-108] diffusion model. This problem, especially if inter-trial variabilities of parameters are included in the model, is computationally very expensive; the parameter estimation procedure often takes a long time even with today's high-speed computers. The algorithm described here makes the calculation of the cumulative distribution functions for predicted process durations computationally much less expensive. This improvement is achieved by solving the Kolmogorov backward equation numerically instead of employing the previously used closed form solution. Additionally, the algorithm can determine the optimum fit for one of the model parameters (the starting point z) directly, thereby reducing the dimension of the parameter search space by one. The resulting method is shown to be notably faster than the standard (closed-form solution) method for parameter estimation.