Choice between single and multiple reinforcers in concurrent-chains schedules

Pigeons responded on concurrent-chains schedules with equal variable-interval schedules as initial links. One terminal link delivered a single reinforcer after a fixed delay, and the other terminal link delivered either three or five reinforcers, each preceded by a fixed delay. Some conditions included a postreinforcer delay after the single reinforcer to equate the total durations of the two terminal links, but other conditions did not include such a postreinforcer delay. With short initial links, preference for the single-reinforcer alternative decreased when a postreinforcer delay was present, but with long initial links, the postreinforcer delays had no significant effect on preference. In conditions with a postreinforcer delay, preference for the single-reinforcer alternative frequently switched from above 50% to below 50% as the initial links were lengthened. This pattern of results was consistent with delay-reduction theory (Squires & Fantino, 1971), but not with the contextual-choice model (Grace, 1994) or the hyperbolic value-added model (Mazur, 2001) as they have usually been applied. However, the hyperbolic value-added model could account for the results if its calculations were expanded to include reinforcers delivered in later terminal links. The implications of these findings for models of concurrent-chains performance are discussed.     

Simulating single word processing in the classic aphasia syndromes based on the Wernicke-Lichtheim-Geschwind theory

The Wernicke-Lichtheim-Geschwind (WLG) theory of the neurobiological basis of language is of great historical importance, and it continues to exert a substantial influence on most contemporary theories of language in spite of its widely recognized limitations. Here, we suggest that neurobiologically grounded computational models based on the WLG theory can provide a deeper understanding of which of its features are plausible and where the theory fails. As a first step in this direction, we created a model of the interconnected left and right neocortical areas that are most relevant to the WLG theory, and used it to study visual-confrontation naming, auditory repetition, and auditory comprehension performance. No specific functionality is assigned a priori to model cortical regions, other than that implicitly present due to their locations in the cortical network and a higher learning rate in left hemisphere regions. Following learning, the model successfully simulates confrontation naming and word repetition, and acquires a unique internal representation in parietal regions for each named object. Simulated lesions to the language-dominant cortical regions produce patterns of single word processing impairment reminiscent of those postulated historically in the classic aphasia syndromes. These results indicate that WLG theory, instantiated as a simple interconnected network of model neocortical regions familiar to any neuropsychologist/neurologist, captures several fundamental "low-level" aspects of neurobiological word processing and their impairment in aphasia.     

The Social Ecological Model and Physical Activity in African American Women

Little is known about the social and contextual correlates (e.g., social norms, environment, social networks, and organizational support) influencing the adoption and maintenance of regular physical activity among minority and underserved populations. The purpose of this review was to apply the social ecological model to better understand physical activity among African American women. A review of the literature pertaining to correlates of physical activity among African American women was conducted and applied to a social ecological perspective. Understanding and addressing social and contextual correlates of physical activity behavior among African American women are necessary to establish comprehensive programs, particularly within community settings. The social ecological model provides a strong theoretical basis to guide physical activity intervention in this population.     

The relationship between anxiety sensitivity and latent symptoms of emotional problems: A structural equation modeling approach

A large body of research suggests that common and specific psychopathology dimensions underlie the symptoms that occur within mood and anxiety disorders. As of yet, it is unclear precisely how the facets of Anxiety Sensitivity (AS), or fear of the symptoms of fear and anxiety, relate to these latent factors. Using data from 606 adolescents participating in the baseline phase of a longitudinal study on risk factors for emotional disorders, we modeled the facets of AS as measured by the Anxiety Sensitivity Index-Expanded Form (ASI-X) and related these facets to a hierarchical model of latent symptoms of psychological distress. Results suggest that one facet of AS is associated with a broad General Distress factor underlying symptoms of most emotional disorders while others relate to intermediate-level and conceptually-meaningful narrow factors representing aspects of psychological distress specific to particular emotional disorders.     

Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task

The purpose of the popular Iowa gambling task is to study decision making deficits in clinical populations by mimicking real-life decision making in an experimental context. Busemeyer and Stout [Busemeyer, J. R., & Stout, J. C. (2002). A contribution of cognitive decision models to clinical assessment: Decomposing performance on the Bechara gambling task. Psychological Assessment, 14, 253-262] proposed an “Expectancy Valence” reinforcement learning model that estimates three latent components which are assumed to jointly determine choice behavior in the Iowa gambling task: weighing of wins versus losses, memory for past payoffs, and response consistency. In this article we explore the statistical properties of the Expectancy Valence model. We first demonstrate the difficulty of applying the model on the level of a single participant, we then propose and implement a Bayesian hierarchical estimation procedure to coherently combine information from different participants, and we finally apply the Bayesian estimation procedure to data from an experiment designed to provide a test of specific influence.     

On the statistical and theoretical basis of signal detection theory and extensions: Unequal variance, random coefficient, and mixture models

Basic results for conditional means and variances, as well as distributional results, are used to clarify the similarities and differences between various extensions of signal detection theory (SDT). It is shown that a previously presented motivation for the unequal variance SDT model (varying strength) actually leads to a related, yet distinct, model. The distinction has implications for other extensions of SDT, such as models with criteria that vary over trials. It is shown that a mixture extension of SDT is also consistent with unequal variances, but provides a different interpretation of the results; mixture SDT also offers a way to unify results found across several types of studies.     

School profiles of at-risk student concentration: Differential growth in oral reading fluency

The present study provides a data-driven approach to identifying groups of schools based on the concentration of at-risk students the school serves. The percentage of English language learners, minority students, and students eligible for free or reduced priced lunch were used as indicators in a latent profile analysis of 569 schools. The goal of the present study was to determine whether school-level average student reading performance varied as a function of the groups identified in the latent profile analysis. To do so, groups extracted by the latent profile analysis were used as school-level predictors of growth in oral reading fluency, which was modeled at the within-student level of a three-level hierarchical growth curve model. Oral reading fluency was measured at four points during the year in a large cross-sectional sample of first-, second-, and third-grade students. Results indicated that schools were able to be classified into four distinct groups based on their concentrations and types of at-risk students. Further, in all three grades, there were significant differences between the four identified groups observed in average reading fluency scores at the beginning of the year, the end of the year, and growth during the year indicating that groups based on school-concentration of at-risk students were significantly related to average student achievement in reading ability.     

Applying memories of reinforcement outcomes mainly to Pavlovian conditioning

A theory devised initially on the basis of instrumental reward schedule data, such as the PREE, was extended to deal with various Pavlovian findings. These Pavlovian findings include blocking, unblocking, relative validity, positive and negative patterning, renewal, reinstatement, reacquisition, and inhibition. In addition, the sequential model was discussed in relation to the rule-learning view of Hulse and Dorsky (1977) employing data from a report by Bloom and Capaldi (1961).     

A Signal Detection Model for Multiple-Choice Exams

A model for multiple-choice exams is developed from a signal-detection perspective. A correct alternative in a multiple-choice exam can be viewed as being a signal embedded in noise (incorrect alternatives). Examinees are assumed to have perceptions of the plausibility of each alternative, and the decision process is to choose the most plausible alternative. It is also assumed that each examinee either knows or does not know each item. These assumptions together lead to a signal detection choice model for multiple-choice exams. The model can be viewed, statistically, as a mixture extension, with random mixing, of the traditional choice model, or similarly, as a grade-of-membership extension. A version of the model with extreme value distributions is developed, in which case the model simplifies to a mixture multinomial logit model with random mixing. The approach is shown to offer measures of item discrimination and difficulty, along with information about the relative plausibility of each of the alternatives. The model, parameters, and measures derived from the parameters are compared to those obtained with several commonly used item response theory models. An application of the model to an educational data set is presented.     

生涯适应力的作用：个体与组织层的跨层面分析*

生涯适应力(career adaptability)是生涯建构理论提出的自我职业生涯管理的核心概念,但国外理论和实践一直认为生涯适应力是一把双刃剑(生涯适应力高的员工工作绩效高,但其离职意向也高),本研究将对此进行检验;同时,生涯适应力作为个体职业生涯开发的核心变量,它在组织职业生涯管理跨层面作用中的价值也未曾研究。通过员工在两个时间点自评和管理者他评问卷,获得54家单位的485份有效调查问卷。结构方程模型分析的结果表明,生涯适应力不仅与工作绩效有显著正相关,而且也与离职意向有显著负相关。层次回归分析结果表明,工龄是生涯适应力与离职意向、工作绩效关系的调节变量;也就是说,工龄短员工的生涯适应力与工作绩效呈显著正相关,与离职意向呈显著负相关,但工龄长员工的生涯适应力与二者的关系都不显著。基于跨层面研究设计,多层线性模型(HLM)分析的结果表明,生涯适应力是组织职业生涯管理与个体工作绩效之间的完全中介变量,但在组织职业生涯管理与离职意向之间的中介作用不显著。这不但回答了生涯适应力对组织价值的管理困境问题,也解决了组织职业生涯管理与个体工作绩效的连接纽带问题。