The use of latent class models for assessing prerequisite relations and transference among traits

This paper presents a strategy for pairwise assessment which may be used to evaluate the nature of both prerequisite and transference relations existing among a set of traits. This strategy is appropriate for use both within a confirmatory context, in which an attempt is made to establish the validity of some specified set of relations among traits, as well as within an exploratory context, in which a search is made for unconjectured prerequisite and transference relations existing between pairs of traits. Both uses of this strategy are based on a variety of latent class models which are representative of various possible relational states existing between pairs of traits. Thus, the nature of trait relations may be investigated through the use of statistical assessments of both absolute and relative fit attained by these models. An application is presented to exemplify how this strategy may be used within the exploratory context.The author is obliged to Clifford Clogg, C. Mitchell, Dayton, and William Schafer for helpful comments made regarding a previous draft of this paper as well as to Mary Papageorgiou who provided access to the data which was considered in this study.     

On Herrnstein's equation and related forms

In 1970, Herrnstein proposed a simple equation to describe the relation between response and reinforcement rates on interval schedules. Its empirical basis is firm, but its theoretical foundation is still uncertain. Two approaches to the derivation of Herrnstein's equation are discussed. It can be derived as the equilibrium solution to a process model equivalent to familiar linear-operator learning models. Modifications of this approach yield competing power-function formulations. The equation can also be derived from the assumption that response strength is proportional to reinforcement rate, given that there is a ceiling on response rate. The proportional relation can, in turn, be derived from a threshold assumption equivalent to Shimp's “momentary maximizing”. This derivation implies that the two parameters of Herrnstein's equation should be correlated, and may explain its special utility in application to internal schedules.     

Fitting cross-classification table data to models when observations are subject to classification error

Individuals are classified in a cross-classification table where two behavioral observations on each individual determine the classification. The problem is to test certain structural models assumed to underlie the cross-classified observations. A minimum chi-square test procedure is proposed.     

Transformation of a three-mode multidimensional scaling solution to indscal form

Relations between Tucker's three-mode multidimensional scaling and Carroll and Chang's INDSCAL are discussed. The possibility is raised that it may be profitable to attempt to transform a three-mode solution to the general form of an INDSCAL solution. Operationally, this involves transforming the three-mode core matrix so that each section is, as nearly as possible, a diagonal matrix. A technique is developed for accomplishing such a transformation, and is applied to two sets of data from the literature. Results indicate that the process is both feasible and valuable, providing useful information on the relative appropriateness of the two models.     

How a high working memory capacity can increase proactive interference

Previous findings suggested that a high working memory capacity (WMC) is potentially associated with a higher susceptibility to proactive interference (PI) if the latter is measured under high cognitive load. To explain such a finding, we propose to consider susceptibility to PI as a net effect of individual executive processes and the intrinsic potential for PI. With the latter, we refer to the amount of information that is activated at a given time and that has the potential to exert PI subsequently. In two studies deploying generalized linear mixed models, susceptibility to PI was modeled as the decline of performance over trials of a complex span task. The results revealed that a higher WMC was associated with a higher susceptibility to PI. Moreover, the number of stimuli recalled in one trial as a proxy variable for the intrinsic potential for PI negatively affected memory performance in the subsequent trial.     

Childhood Maltreatment,Emotional Response Inhibition,and Suicide in Psychiatric Inpatients

Childhood abuse and/or neglect adversely influences development of neurocognitive systems that regulate affect and behavior. Poor inhibitory control over emotional reactions is thus one potential pathway from maltreatment to suicide. Adult psychiatric inpatients completed the Childhood Trauma Questionnaire and an emotional stop-signal task indexing negative emotional action termination (NEAT): the ability to inhibit ongoing motor reactions to aversive stimuli triggered by negative affect. Clinical interviews assessed suicidal thoughts and behaviors during hospitalization (n = 131) and at follow-up assessments 6 months later (n = 87). Our primary aim was to examine whether maltreatment history and NEAT explain overlapping variance in suicidal behaviors (1) retrospectively and (2) 6 months following hospital discharge. Contrary to prediction, childhood maltreatment was unrelated to history of suicidal behaviors. However, NEAT was consistently associated with prior suicidal acts, even controlling for suicidal ideation and demographic covariates. NEAT similarly contributed to the prediction of post-discharge suicidal behaviors, whereas we found no effect of maltreatment history. The present study suggests that NEAT captures suicide risk independently of childhood maltreatment. Results implicated NEAT impairment specifically, rather than broader response inhibition deficits (e.g., to positive stimuli), in past and future suicidal behaviors. These findings provide preliminary support for NEAT as a behavioral vulnerability marker for suicide, with implications for understanding links between maltreatment history and suicidal acts.     

A note on computing Louis’ observed information matrix identity for IRT and cognitive diagnostic models

Using Louis’ formula, it is possible to obtain the observed information matrix and the corresponding large-sample standard error estimates after the expectation–maximization (EM) algorithm has converged. However, Louis’ formula is commonly de-emphasized due to its relatively complex integration representation, particularly when studying latent variable models. This paper provides a holistic overview that demonstrates how Louis’ formula can be applied efficiently to item response theory (IRT) models and other popular latent variable models, such as cognitive diagnostic models (CDMs). After presenting the algebraic components required for Louis’ formula, two real data analyses, with accompanying numerical illustrations, are presented. Next, a Monte Carlo simulation is presented to compare the computational efficiency of Louis’ formula with previously existing methods. Results from these presentations suggest that Louis’ formula should be adopted as a standard method when computing the observed information matrix for IRT models and CDMs fitted with the EM algorithm due to its computational efficiency and flexibility.     

Using a Fork as a Hairbrush: Investigating Dual Routes to Release from Functional Fixedness

Functional fixedness involves difficulty with conceptualizing creative object uses. When it obstructs problem‐solving, individuals must reframe their approach. We examined how different training techniques—chunk decomposition (i.e., considering an object’s basic parts and physical properties) and constraint relaxation (i.e., considering an object’s different functions)—might rely upon different routes to creative reframing. Additionally, we investigated how different forms of cognitive load interact with these dual routes. Participants learned one of three techniques. Chunk decomposition participants created object breakdown diagrams; constraint relaxation participants created object functions lists; and free association (control) participants wrote a word that they associated with each of several concrete nouns. After training, participants attempted to solve five functional fixedness problems. E1 investigated how increasing germane cognitive load via either direct or indirect prompting affected training transfer. Experiment 2 investigated how reducing extraneous cognitive load by providing no transfer instructions and using an eye‐closure strategy. Across both experiments, results supported differences in accuracy and response latency by training. However, chunk decomposition and constraint relaxation did not follow the same pattern, suggesting different mechanisms of the effect. We discuss possible applications to increase innovation in real‐world domains such as education, business, and engineering.     

The role of empathy and social anxiety in Latinx adolescents' indirect peer aggression during the transition to high school

The primary purpose of this study was to evaluate the relationship between decreased empathy (i.e., cognitive and affective) and indirect and cyber peer aggression among Latinx adolescents during their transition to high school. Further, we examined the degree to which social anxiety moderated this relationship. Participants were 469 Latinx ninth graders, ages 13–17 years (M = 14.52, SD = 0.58; 58% girls). Adolescents completed the Revised Peer Experiences Questionnaire, Cyber Peer Experiences Questionnaire, Basic Empathy Scale, and Social Anxiety Scale for Adolescents at two different time points, 3 months apart. Hierarchical linear regression analyses revealed concurrent and prospective relationships between lower cognitive empathy and the perpetration of both indirect and cyber aggression. In addition, social anxiety moderated the concurrent associations between both types of empathy and both types of aggression perpetration. Results suggest that interventions that facilitate cognitive empathy and decrease social anxiety may help to reduce adolescents' indirect and cyber aggression toward peers throughout the high school transition.     

The impact of demographics and nutritional status on cognitive functioning in an Iranian adults sample

This study investigated the impact of demographic variables and nutritional status on adult cognitive functioning using structural equation modeling. Demographic variables that were considered were height, weight and gender, whilst nutritional status was measured on the Nutrition Assessment Inventory (NAI). Cognitive functions, such as executive cognitive functions, cognitive flexibility, cognitive ability and cognitive vulnerability were measured using the Amsterdam Executive Function Inventory (AEFI), the Cognitive Flexibility Scale (CFS), the Cognitive Ability Questionnaire (CAQ), and the Dysfunctional Attitude Scale Form A-Revised (DAS-A-R) respectively. Findings indicated that ethnicity and weight variables contribute to 8.8% of the nutritional status variations observed. A SEM analysis showed that nutritional status has an impact on 13% on the measured cognitive abilities of adults. The effects of “healthy nutrition”, “use of complementary nutritients”, “coping with high fat foods”, and “high fat food assumption” subscales of the nutrition scale were found to play a role in cognitive ability. This study shows a fitted SEM for the predictive roles of ethnicity, weight and nutritional status on the cognitive ability in adults.