A neurocognitive and socioecological model of self-awareness

In the past, researchers have focused mainly on the effects and consequences of self-awareness; however, they have neglected a more basic issue pertaining to the specific mechanisms that initiate and sustain self-perception. The author presents a model of self-awareness that proposes the existence of 3 sources of self-information. First, the social milieu includes early face-to-face interactions, self-relevant feedback, a social comparison mechanism that leads to perspective taking, and audiences. Second, contacts with objects and structures in the physical environment foster self-world differentiation in infants; this environment also contains self-focusing and reflecting stimuli, such as mirrors and video cameras. Third, the self can develop bodily awareness through proprioception and can reflect on itself using imagery and inner speech. Furthermore, self-awareness is mainly mediated by the prefrontal lobes. The author establishes various links among these different neurological, social, ecological, and cognitive elements of the model.     

Marginal maximum likelihood estimation for a psychometric model of discontinuous development

Item response theory models posit latent variables to account for regularities in students' performances on test items. Wilson's “Saltus” model extends the ideas of IRT to development that occurs in stages, where expected changes can be discontinuous, show different patterns for different types of items, or even exhibit reversals in probabilities of success on certain tasks. Examples include Piagetian stages of psychological development and Siegler's rule-based learning. This paper derives marginal maximum likelihood (MML) estimation equations for the structural parameters of the Saltus model and suggests a computing approximation based on the EM algorithm. For individual examinees, empirical Bayes probabilities of learning-stage are given, along with proficiency parameter estimates conditional on stage membership. The MML solution is illustrated with simulated data and an example from the domain of mixed number subtraction. The authors' names appear in alphabetical order. We would like to thank Karen Draney for computer programming, Kikumi Tatsuoka for allowing us to use the mixed-number subtraction data, and Eric Bradlow, Chan Dayton, Kikumi Tatsuoka, and four anonymous referees for helpful suggestions. The first author's work was supported by Contract No. N00014-88-K-0304, R&T 4421552, from the Cognitive Sciences Program, Cognitive and Neural Sciences Division, Office of Naval Research, and by the Program Research Planning Council of Educational Testing Service. The second author's work was supported by a National Academy of Education Spencer Fellowship and by a Junior Faculty Research Grant from the Committee on Research, University of California at Berkeley. A copy of the Saltus computer program can be obtained from the second author.     

四参数Logistic模型潜在特质参数的Warm加权极大似然估计

本文以四参数Logistic(4-parameter Logistic,4PL)模型为研究对象,根据Warm的加权极大似然估计技巧,提出了4PL模型潜在特质参数的加权极大似然估计方法,并借助模拟研究对加权极大似然估计的性质进行验证。研究结果表明,与通常的极大似然估计和后验期望估计相比,加权极大似然估计的偏差(bias)明显减小,并且具有良好的返真性能。此外,在测试的长度较短和项目的区分度较小的情况下,加权极大似然估计依然保持了良好的统计性质,表现出更加显著的优势。     

Constrained maximum likelihood estimation of two-level covariance structure model via EM type algorithms

In this paper, the constrained maximum likelihood estimation of a two-level covariance structure model with unbalanced designs is considered. The two-level model is reformulated as a single-level model by treating the group level latent random vectors as hypothetical missing-data. Then, the popular EM algorithm is extended to obtain the constrained maximum likelihood estimates. For general nonlinear constraints, the multiplier method is used at theM-step to find the constrained minimum of the conditional expectation. An accelerated EM gradient procedure is derived to handle linear constraints. The empirical performance of the proposed EM type algorithms is illustrated by some artifical and real examples.This research was supported by a Hong Kong UCG Earmarked Grant, CUHK 4026/97H. We are greatly indebted to D.E. Morisky and J.A. Stein for the use of their AIDS data in our example. We also thank the Editor, two anonymous reviewers, W.Y. Poon and H.T. Zhu for constructive suggestions and comments in improving the paper. The assistance of Michael K.H. Leung and Esther L.S. Tam is gratefully acknowledged.     

Marginal maximum likelihood estimation of item response theory (IRT) equating coefficients for the common-examinee design

A method of estimating item response theory (IRT) equating coefficients by the common-examinee design with the assumption of the two-parameter logistic model is provided. The method uses the marginal maximum likelihood estimation, in which individual ability parameters in a common-examinee group are numerically integrated out. The abilities of the common examinees are assumed to follow a normal distribution but with an unknown mean and standard deviation on one of the two tests to be equated. The distribution parameters are jointly estimated with the equating coefficients. Further, the asymptotic standard errors of the estimates of the equating coefficients and the parameters for the ability distribution are given. Numerical examples are provided to show the accuracy of the method.     

Consistent estimation in the rasch model based on nonparametric margins

Consider the class of two parameter marginal logistic (Rasch) models, for a test ofm True-False items, where the latent ability is assumed to be bounded. Using results of Karlin and Studen, we show that this class of nonparametric marginal logistic (NML) models is equivalent to the class of marginal logistic models where the latent ability assumes at most (m + 2)/2 values. This equivalence has two implications. First, estimation for the NML model is accomplished by estimating the parameters of a discrete marginal logistic model. Second, consistency for the maximum likelihood estimates of the NML model can be shown (whenm is odd) using the results of Kiefer and Wolfowitz. An example is presented which demonstrates the estimation strategy and contrasts the NML model with a normal marginal logistic model.This research was supported by NIMH traning grant, 2 T32 MH 15758-06 and by ONR contract N00014-84-K-0588. The author would like to thank Diane Lambert, John Rolph, and Stephen Fienberg for their assistance. Also, the comments of the referees helped to substantially improve the final version of this paper.     

A maximum likelihood hierarchical disaggregate model for predicting choices of individuals

The absence of operational disaggregate lexicographic decision models and Tversky's observation that choice behavior is often inconsistent, hierarchical, and context dependent motivate the development of a maximum likelihood hierarchical (MLH) choice model. This new disaggregate choice model requires few assumptions and accommodates the three aspects of choice behavior noted by A. Tversky (1972, Journal of Mathematical Psychology, 9, 341–367). The model has its foundation in a prototype model developed by the authors. Unlike the deterministic prototype, however, MLH is a probabilistic model which generates maximum likelihood estimators of the aggregate “cutoff values.” The model is formulated as a concave programming problem whose solutions are therefore globally optimal. Finally, the model is applied to data from three separate studies where it is demonstrated to have superior performance over the prototype model in its predictive performance.     

A computational model of retrospective time estimation

Retrospective time estimation is an important aspect of dynamic systems and needs to be integrated in cognitive architectures. This article gives an overview of theoretical accounts of retrospective and prospective time estimation. Assumptions based on an experiment investigating retrospective time estimation conducted in our research group are presented. Integrating both we introduce a retrospective timer-module for ACT-R 6.0 and the corresponding estimation algorithm. The successful validation of the module is shown and further implications are discussed.     

A neurocognitive model of the ethical decision-making process: implications for study and practice

The field of business ethics is entrenched in a cognitive approach that portrays the ethical decision-making process as a completely deliberate and reasoned exercise. In light of growing concerns about the veracity of this approach, I build upon current knowledge of how the brain functions to present a neurocognitive model of ethical decision making. The model suggests that ethical decision making involves 2 interrelated yet functionally distinct cycles, a reflexive pattern matching cycle and a higher order conscious reasoning cycle, and thereby describes not only reasoned analysis, but also the intuitive and retrospective aspects of ethical decision making. The model sparks research in new areas, holds significant implications for the study of ethical decision making, and provides suggestions for improving ethical behavior in organizations.     

A model of fixed activation time scheduling

A model for the fixed activation time scheduling of events is presented. Activation time is defined as the time needed for an event to regain dominance in the stream of events measured from the point in time at which it lost dominance. The fixed activation time scheduling rule states that some event must be ongoing at all times, that an ongoing event will continue until interrupted by another event, that every event has a predetermined activation time and that fulfilling the activation time requirement is the necessary and sufficient condition for an event to interrupt an ongoing event. The last condition sets this rule apart from those employed in quequeing theory since it does not allow events to be completed or queues to form. Derivations from the model concerning the dynamic organization of the stream of events, written in terms of the frequency and duration of events and the transitions between pairs of events, are given. Special attention is paid to issues that arise in deciding on the coding of events. It is suggested that the fixed activation time scheduling rule will apply to a wide variety of settings, environmental and behavioral, and this is illustrated by a detailed application of the model to observations on the stream of free behavior.     

A note on the estimation of test reliability by the Kuder-Richardson formula (20)

The Kuder-Richardson formula (20) is rewritten to be identical with the simplest formula, (21), except for the addition of a term involving the standard deviation, _p , of the itemp's. If _p can be estimated, a rapid and superior estimate of test reliability is possible in contrast to the simpler formula (21) used when the number of items and mean and standard deviation of test scores are known.Kuder, G. F. and Richardson, M. W. The theory of the estimation of test reliability.Psychometrika. 1937, 2, 151–160.     

The five factor model of personality and alexithymia: A meta-analysis

The main objective of the study was to examine the relationship between the Five Factor Model of Personality and alexithymia. Data were collected from 25 studies, which included 30 independent samples, 1384 effect sizes, and 7440 participants. All analyses were conducted with random effects models. Greater neuroticism and lower extraversion, openness to experience, agreeableness, and conscientiousness were associated with higher cognitive alexithymia. Greater neuroticism and openness to experience were linked to lower affective alexithymia. Additionally, age moderated the relationship between the Five Factor Model of Personality and cognitive alexithymia, in that the association between neuroticism and alexithymia became stronger with age whereas the relations of extraversion, openness to experience, agreeableness, and conscientiousness with alexithymia became weaker with age.     

Autonomic and EEG patterns during eyes-closed rest and transcendental meditation (TM) practice: the basis for a neural model of TM practice.

In this single-blind within-subject study, autonomic and EEG variables were compared during 10-min, order-balanced eyes-closed rest and Transcendental Meditation (TM) sessions. TM sessions were distinguished by (1) lower breath rates, (2) lower skin conductance levels, (3) higher respiratory sinus arrhythmia levels, and (4) higher alpha anterior-posterior and frontal EEG coherence. Alpha power was not significantly different between conditions. These results were seen in the first minute and were maintained throughout the 10-min sessions. TM practice appears to (1) lead to a state fundamentally different than eyes-closed rest; (2) result in a cascade of events in the central and autonomic nervous systems, leading to a rapid change in state (within a minute) that was maintained throughout the TM session; and (3) be best distinguished from other conditions through autonomic and EEG alpha coherence patterns rather than alpha power. Two neural networks that may mediate these effects are suggested. The rapid shift in physiological functioning within the first minute might be mediated by a "neural switch" in prefrontal areas inhibiting activity in specific and nonspecific thalamocortical circuits. The resulting "restfully alert" state might be sustained by a basal ganglia-corticothalamic threshold regulation mechanism automatically maintaining lower levels of cortical excitability.     

Psychometric validation of an Organisational Performance Questionnaire (OPQ) based on the Burke-Litwin model

This study reports the findings on the development and validation of an Organisational Performance Questionnaire (OPQ) based on the Burke-Litwin model. Respondents were 398 employees from various public and private sector organisations in South Africa, consisting of different genders (male = 60.8%, female = 39.2%), different functional groupings (mostly operations, finance, human relations = 37.25%) and mostly middle or senior level managers (62.4%). Data were analysed utilising exploratory factor analysis with promax rotation. Results indicated the OPQ to measure all twelve of the Burke-Litwin elements contained in their model: external environment, mission and strategy, leadership, culture, structure, management practices, systems, work group climate, skills/job match, individual needs and values, motivation, and organisational and individual performance. An OPQ based on the Burke-Litwin model appears valid for assessing organisational performance in the South African setting.     

A knowledge-resonance (KRES) model of category learning

This article introduces a connectionist model of category learning that takes into account the prior knowledge that people bring to new learning situations. In contrast to connectionist learning models that assume a feedforward network and learn by the delta rule or backpropagation, this model, the knowledge-resonance model, or KRES, employs a recurrent network with bidirectional symmetric connection whose weights are updated according to a contrastive Hebbian learning rule. We demonstrate that when prior knowledge is represented in the network, KRES accounts for a considerable range of empirical results regarding the effects of prior knowledge on category learning, including (1) the accelerated learning that occurs in the presence of knowledge, (2) the better learning in the presence of knowledge of category features that are not related to prior knowledge, (3) the reinterpretation of features with ambiguous interpretations in light of error-corrective feedback, and (4) the unlearning of prior knowledge when that knowledge is inappropriate in the context of a particular category.