Limited information estimation and testing of discretized multivariate normal structural models

Discretized multivariate normal structural models are often estimated using multistage estimation procedures. The asymptotic properties of parameter estimates, standard errors, and tests of structural restrictions on thresholds and polychoric correlations are well known. It was not clear how to assess the overall discrepancy between the contingency table and the model for these estimators. It is shown that the overall discrepancy can be decomposed into a distributional discrepancy and a structural discrepancy. A test of the overall model specification is proposed, as well as a test of the distributional specification (i.e., discretized multivariate normality). Also, the small sample performance of overall, distributional, and structural tests, as well as of parameter estimates and standard errors is investigated under conditions of correct model specification and also under mild structural and/or distributional misspecification. It is found that relatively small samples are needed for parameter estimates, standard errors, and structural tests. Larger samples are needed for the distributional and overall tests. Furthermore, parameter estimates, standard errors, and structural tests are surprisingly robust to distributional misspecification. This research was supported by the Department of Universities, Research and Information Society (DURSI) of the Catalan Government, and by grants BSO2000-0661 and BSO2003-08507 of the Spanish Ministry of Science and Technology.     

How to, and how not to, bridge computational cognitive neuroscience and Husserlian phenomenology of time consciousness

A number of recent attempts to bridge Husserlian phenomenology of time consciousness and contemporary tools and results from cognitive science or computational neuroscience are described and critiqued. An alternate proposal is outlined that lacks the weaknesses of existing accounts.     

利用组织工程治疗骨缺损中的几点问题

骨缺损是临床上的常见病,也是骨科治疗的难题之一。近年来,骨组织工程发展迅速,利用骨组织工程治疗骨缺损成为研究的热点。组织工程应用的主要问题在于种子细胞的培养和细胞种植基质材料的优化。在此领域的发展过程中,渗透着丰富的哲学思想,理解和把握这些哲学思想对完善利用骨组织工程治疗骨缺损的工作将大有益处。     

Are unsupervised neural networks ignorant? Sizing the effect of environmental distributions on unsupervised learning

Learning environmental biases is a rational behavior: by using prior odds, Bayesian networks rapidly became a benchmark in machine learning. Moreover, a growing body of evidence now suggests that humans are using base rate information. Unsupervised connectionist networks are used in computer science for machine learning and in psychology to model human cognition, but it is unclear whether they are sensitive to prior odds. In this paper, we show that hard competitive learners are unable to use environmental biases while recurrent associative memories use frequency of exemplars and categories independently. Hence, it is concluded that recurrent associative memories are more useful than hard competitive networks to model human cognition and have a higher potential in machine learning.     

A molar view of goal direction and habit

When we treat behavior within an evolutionary framework and as temporally extended flow, two fundamental questions arise: (a) What is an organism? and (b) What is behavior? An organism is a process that stays intact by constantly exchanging energy with the environment. It takes in resources and puts out waste. The behavior of an organism consists of those process parts of the organism process that make up the exchange. These activities serve the function of reproducing, which generally depends on surviving. Surviving and reproducing depend on responding to phylogenetically important events (PIEs). A PIE induces activities that enhance or mitigate the PIE. Organisms respond not only to a PIE but also to events that covary with the PIE. Both activities and environmental features may covary with a PIE. When either type of covariance is introduced to an organism, behavior adapts over time. The early stages of adaptation constitute what researchers call “goal direction,” and the later stages constitute what researchers call “habit.” Behavior and environment constitute a dynamic system, and manipulations of the covariances and environmental features of the system allow many experimental interventions. This molar approach allows experiments on goal direction and habit to be understood without appeal to everyday mentalistic terms.     

The effects of task-irrelevant threatening stimuli on orienting- and executive attentional processes under cognitive load

Human visual attention is biased to rapidly detect threats in the environment so that our nervous system can initiate quick reactions. The processes underlying threat detection (and how they operate under cognitive load), however, are still poorly understood. Thus, we sought to test the impact of task-irrelevant threatening stimuli on the salience network and executive control of attention during low and high cognitive load. Participants were exposed to neutral or threatening pictures (with moderate and high arousal levels) as task-irrelevant distractors in near (parafoveal) and far (peripheral) positions while searching for numbers in ascending order in a matrix array. We measured reaction times and recorded eye-movements. Our results showed that task-irrelevant distractors primarily influenced behavioural measures during high cognitive load. The distracting effect of threatening images with moderate arousal level slowed reaction times for finding the first number. However, this slowing was offset by high arousal threatening stimuli, leading to overall shorter search times. Eye-tracking measures showed that participants fixated threatening pictures more later and for shorter durations compared to neutral images. Together, our results indicate a complex relationship between threats and attention that results not in a unitary bias but in a sequence of effects that unfold over time.     

Empirical underidentification in estimating random utility models: The role of choice sets and standardizations

A standard approach to distinguishing people’s risk preferences is to estimate a random utility model using a power utility function to characterize the preferences and a logit function to capture choice consistency. We demonstrate that with often-used choice situations, this model suffers from empirical underidentification, meaning that parameters cannot be estimated precisely. With simulations of estimation accuracy and Kullback–Leibler divergence measures we examined factors that potentially mitigate this problem. First, using a choice set that guarantees a switch in the utility order between two risky gambles in the range of plausible values leads to higher estimation accuracy than randomly created choice sets or the purpose-built choice sets common in the literature. Second, parameter estimates are regularly correlated, which contributes to empirical underidentification. Examining standardizations of the utility scale, we show that they mitigate this correlation and additionally improve the estimation accuracy for choice consistency. Yet, they can have detrimental effects on the estimation accuracy of risk preference. Finally, we also show how repeated versus distinct choice sets and an increase in observations affect estimation accuracy. Together, these results should help researchers make informed design choices to estimate parameters in the random utility model more precisely.     

Analyzing individual differences in vocational, leisure, and family interests: A multitrait-multimethod approach

This study investigates the latent structure of individual differences in vocational, leisure, and family interests. The participants consisted of 302 French adults who rated their like or dislike for activities based on Holland’s RIASEC typology and presented in three life domains: work, family and leisure. The multitrait-multimethod model proposed by Eid [Eid, M. (2000). A multitrait-multimethod model with minimal assumptions. Psychometrika 65, 241-261.] was used with the vocational interests as standard comparison, and was applied separately on each of the 6 RIASEC types. Results indicated that interests strongly intercorrelated whatever their vocational vs. leisure or family contextualization. However, since these correlations were controlled for measurement error, the results also suggested that the effects of these contextualizations of the activities could not be ignored because they accounted for a non negligible part of the variance for several activities. Theoretical and practical implications are discussed and directions for future research are presented.     

Dysfunctional implications of narrow window theory: variability in the intuitive assessment of correlation

Narrow Window theory, suggested by Y. Kareev ten years ago, has so far focused on one central implication of the limited capacity of working memory on intuitive correlation estimation, namely, overestimation of the distal population correlation. This paper points to additional and perhaps more dramatic implications due to the large dispersion of intuitive estimates: (a) large estimation errors, possibly causing overestimation of negligible rhos, misses of strong rhos, and distorted hierarchies of the rhos between different pairs of variables; and (b) large interpersonal differences in the estimation of any given rho and highly incongruent hierarchies of estimated correlations between different pairs of variables. These implications impede both individuals' adaptation to the empirical world and communication among themselves.     

儿童数字估计的表征模式与发展

探讨中国儿童数字估计的表征模式与发展趋势。包括两个实验,均采用数字线估计任务,实验一以92名幼儿园、一年级及二年级儿童为被试,考察其在0~100范围的数字估计,结果显示,幼儿园儿童在数字估计更多地采用对数表征,而一二年级的儿童在数字估计中更多地采用线性表征;实验二以86名一、三、五年级儿童为被试,考察其在0~1000范围的数字估计,结果显示,一年级儿童有一半采用对数表征,另一半采用线性表征,而三五年级儿童大多采用线性表征。中国儿童的数字估计表现出与美国儿童相同的发展模式,都是由不精确的对数表征逐步向精确的线性表征发展;人的数表征有多种形式,即使在同一年龄阶段,也会因任务难度的不同而选择不同的表征模式。中国儿童精确数字估计能力的出现要早于美国儿童。