Combining Item Response Theory and Diagnostic Classification Models: A Psychometric Model for Scaling Ability and Diagnosing Misconceptions

Traditional testing procedures typically utilize unidimensional item response theory (IRT) models to provide a single, continuous estimate of a student’s overall ability. Advances in psychometrics have focused on measuring multiple dimensions of ability to provide more detailed feedback for students, teachers, and other stakeholders. Diagnostic classification models (DCMs) provide multidimensional feedback by using categorical latent variables that represent distinct skills underlying a test that students may or may not have mastered. The Scaling Individuals and Classifying Misconceptions (SICM) model is presented as a combination of a unidimensional IRT model and a DCM where the categorical latent variables represent misconceptions instead of skills. In addition to an estimate of ability along a latent continuum, the SICM model provides multidimensional, diagnostic feedback in the form of statistical estimates of probabilities that students have certain misconceptions. Through an empirical data analysis, we show how this additional feedback can be used by stakeholders to tailor instruction for students’ needs. We also provide results from a simulation study that demonstrate that the SICM MCMC estimation algorithm yields reasonably accurate estimates under large-scale testing conditions.     

A comparison of latent trait and latent class analyses of Likert-type data

This paper brings together and compares two developments in the analysis of Likert attitude scales. The first is the generalization of latent class models to ordered response categories. The second is the introduction of latent trait models with multiplicative parameter structures for the analysis of rating scales. Key similarities and differences between these two methods are described and illustrated by applying a latent trait model and a latent class model to the analysis of a set of life satisfaction data. The way in which the latent trait model defines a unit of measurement, takes into account the order of the response categories, and scales the latent classes, is discussed. While the latent class model provides better fit to these data, this is achieved at the cost of a logically inconsistent assignment of individuals to latent classes.The author wishes to thank Clifford C. Clogg, Otis Dudley Duncan and Benjamin D. Wright for their helpful comments on an earlier version of this paper.     

Examining Factor Score Distributions to Determine the Nature of Latent Spaces

Similarities between latent class models with K classes and linear factor models with K ? 1 factors are investigated. Specifically, the mathematical equivalence between the covariance structure of the two models is discussed, and a Monte Carlo simulation is performed using generated data that represents both latent factors and latent classes with known amounts of overlap. It is shown that, under certain conditions, the distribution of factor scores can be related to the continuity of the latent space via tests of multimodality as suggested by McDonald (1967) McDonald, R. P. 1967. Non-linear factor analysis. Psychometric Monographs, 15 Psychometric Society [Google Scholar].     

Accelerating stimuli for two classes of coercive behaviors

The analyses focused on a means by which classes of events may be derived from sequential data. A prior analyses of family interaction has derived two classes labeled Hostile and Social Aggression. Events in a class were initiated by a common network of antecedent behaviors. The current analyses showed that class members also shared a common set of maintaining consequences. These events correlated with altered probabilities for the immediate recurrence of a target event.     

Creativity and Intelligence Revisited: A Latent Variable Analysis of Wallach and Kogan (1965)

Many decades of research have shown that creativity and intelligence are modestly related. Some studies, however, have found that creativity and intelligence are essentially unrelated. The best example may be Wallach and Kogan's (1965 Wallach , M. A. , & Kogan , N. ( 1965 ). Modes of thinking in young children: A study of the creativity–intelligence distinction . New York : Holt, Rinehart, & Winston . [Google Scholar]) landmark study of 151 children. In that study, 10 measures of creativity didn't correlate with 10 measures of intelligence and academic achievement (average r = .09). The present research reanalyzed these data using latent variable analysis, which can (a) assess the relations between latent creativity and intelligence variables and (b) model method variance shared by the creativity tasks. Consistent with past research, the latent originality and fluency variables significantly predicted intelligence. The relations' magnitude (around r = .20) was consistent with past research, suggesting that Wallach and Kogan's data replicate other studies of creativity and intelligence.     

The Relative Contribution of a Typological versus a Dimensional Approach for Understanding Obsessive-Compulsive Symptoms in Adolescents

In order to better understand the heterogeneous nature of Obsessive-Compulsive (OC) symptoms, a typological or a dimensional approach can be used to structure the variety of symptoms into a set of core components. However, there is still no consensus on which approach is the most robust to predict several OC-related criterion measures, especially in adolescents. From this perspective, the current study empirically identified OC classes (i.e., types), and explored whether types or dimensions are the strongest predictors of adolescent OC-related criterion variables. To identify OC classes, we conducted latent class analysis on the Youth Obsessive-Compulsive Symptoms Scale (YOCSS; De Caluwé and De Clercq 2014) that was completed by 682 community and referred adolescents (71.4 % girls, 12–18 years old, mean age = 15.67, SD = 1.53), and we also computed OC dimension scores as outlined in De Caluwé and De Clercq (2014). We subsequently used hierarchical regression analysis to examine the incremental validity of the OC classes beyond the OC domains, and vice versa, in predicting several OC-related criterion variables that were completed by the adolescents or their mothers (N = 325). The results indicated that the two identified OC classes only differed quantitatively but not qualitatively, hence reflecting severity classes, and also showed that OC domains have significant effects beyond the effects of the OC classes, whereas the reverse did not hold. The dimensional approach appears to have the strongest predictive value for OC symptomatology in adolescents, leading to clinical implications for conceptualization and assessment of obsessive and compulsive problems in younger age groups.     

Hegel,the Trinity,and the ‘I’

The main goal of this paper is to argue the relevance of Hegel’s notion of the Trinity with respect to two aspects of Hegel’s idealism: the overcoming of subjectivism and his conception of the ‘I’. I contend that these two aspects are interconnected and that the Trinity is important to Hegel’s strategy for addressing these questions. I first address the problem of subjectivism by considering Hegel’s thought against the background of modern philosophy. I argue that the recognitive structure of Hegel’s idealism led him to give the Trinity a decisive role in his philosophical account. Next, I discuss the Trinity by analysing the three divine persons. This analysis paves the way for the conclusion, where I argue that the Trinity represents a model for re-thinking the ‘I’ in a way that overcomes a ‘naïve realist’ and a ‘subjective’ account of the self. I suggest that Hegel’s absolute idealism can be conceived as an approach to the ‘I’ that considers the role of acts of mutual recognition for the genesis of self-conscious thought, and that the Trinity is the Darstellung of the relational and recognitive structure of the ‘I’.     

Computation of psychophysical thresholds using the probit technique

Probit analysis is a statistical technique that can be used for the computation of psychophysical thresholds, although it was originally developed for the analysis of pharmacological and toxicological data. Probit analysis may be applied to psychophysical data if the method of constant stimuli has been used for data collection. A computer program written in APPLESOFT BASIC that performs probit analyses on such psychophysical data is presented and explained.     

Assessment of Callous-Unemotional Traits in 6 to 12 Year-Old Children with Oppositional Defiant Disorder/Conduct Disorder by Parent Ratings

The factorial structure of the Inventory of Callous-Unemotional Traits (ICU; Frick 2004) has been inconsistent across previous studies using different rater versions (self-report, parent, teacher) and versions in different languages applied to both clinical and nonreferred samples predominantly of adolescents. The present study examined the factorial structure of the parent-report version of the ICU in a clinical sample of boys aged 6–12 years with Oppositional Defiant Disorder/Conduct Disorder (n?=?131) using confirmatory factor analysis (CFA) and exploratory factor analysis (EFA). Results from the CFA supported previous findings, but even the preferred model with three independent factors (Callousness, Uncaring, and Unemotional) showed inadequate model fit. Subsequent EFA revealed a three-factor model consisting of two new subscales (Callousness/Lack of Guilt or Remorse, Unconcerned about Performance) and the original subscale Unemotional. Internal consistencies of the three subscales and total score were satisfactory, and intercorrelations of the subscales were weak, except for a moderate correlation between the subscales Callousness/Lack of Guilt or Remorse and Unconcerned about Performance. The corresponding subscales of the original and new versions were highly correlated. As expected, the ICU subscale Callousness/Lack of Guilt or Remorse showed associations with other measures of aggressive and oppositional behavior. The other two ICU subscales were not associated with aggression or oppositional/antisocial behavior, but Unconcerned about Performance correlated with a measure of attention problems and Unemotional correlated with the internalizing problem withdrawn. The implications of these findings are discussed, especially as a callous unemotional specifier for the diagnosis of Conduct Disorder is included in DSM-5.     

PSN: A prolog declarative model of conceptual knowledge

This paper introduces a declarative model of semantic memory, called PSN, written in Prolog. It is shown to be a descendant of Quillian’s (1969) Teachable Language Comprehender (TLC) in its structuring of knowledge as a conceptual reticulum and in its use of spreading activation as a retrieval mechanism. PSN goes beyond TLC, however, in its ability to instantiate the essential benchmark properties of human semantic retrieval. As such, it can provide cognitive science with a normative model on which to assess further research and it demonstrates the value of the Prolog language for modeling psychological processes.     

Nothing Persuades Like Success: Reflections on Partially and Over-Successful Persuasion. A Reply to Debowska-Kozlowska

In this brief commentary of Kamila Debowska-Kozlowska’s insightful analysis of persuasive outcomes (Processing topics from the Beneficial Cognitive Model in partially and over-successful persuasion dialogues. Argumentation, 2014), I articulate some suggestions for future development of her ideas. My main claim is that, while instances of partially and over-successful persuasion are indeed worthy of further theoretical inquiry, the topical analysis proposed by Debowska-Kozlowska may benefit from integration with other approaches.     

Risk Patterns and Correlated Brain Activities. Multidimensional Statistical Analysis of fMRI Data in Economic Decision Making Study

Decision making usually involves uncertainty and risk. Understanding which parts of the human brain are activated during decisions under risk and which neural processes underly (risky) investment decisions are important goals in neuroeconomics. Here, we analyze functional magnetic resonance imaging (fMRI) data on 17 subjects who were exposed to an investment decision task from Mohr, Biele, Krugel, Li, and Heekeren (in NeuroImage 49, 2556–2563, 2010b). We obtain a time series of three-dimensional images of the blood-oxygen-level dependent (BOLD) fMRI signals. We apply a panel version of the dynamic semiparametric factor model (DSFM) presented in Park, Mammen, Wolfgang, and Borak (in Journal of the American Statistical Association 104(485), 284–298, 2009) and identify task-related activations in space and dynamics in time. With the panel DSFM (PDSFM) we can capture the dynamic behavior of the specific brain regions common for all subjects and represent the high-dimensional time-series data in easily interpretable low-dimensional dynamic factors without large loss of variability. Further, we classify the risk attitudes of all subjects based on the estimated low-dimensional time series. Our classification analysis successfully confirms the estimated risk attitudes derived directly from subjects’ decision behavior.     

Eight-Year Latent Class Trajectories of Academic and Social Functioning in Children with Attention-Deficit/Hyperactivity Disorder

We examined trajectories of academic and social functioning in children with attention-deficit/hyperactivity disorder (ADHD) to identify those who might be at risk for especially severe levels of academic and social impairment over time. We estimated a series of growth mixture models using data from two subsamples of children participating in the NIMH Collaborative Multisite Multimodal Treatment Study of Children with ADHD (MTA) including those with at least baseline and 96-month data for reading and mathematics achievement (n = 392; 77.3% male; M age = 7.7; SD = 0.8) or social skills ratings from teachers (n = 259; 74.9% male; M age = 7.6; SD = 0.8). We compared latent trajectories for children with ADHD to mean observed trajectories obtained from a local normative (i.e., non-ADHD) comparison group (n = 289; 80.6% male; M age = 9.9; SD = 1.1). Results indicated six latent trajectory classes for reading and mathematics and four classes for teacher social skills ratings. There was not only a relationship between trajectories of inattention symptoms and academic impairment, but also a similarly strong association between trajectory classes of hyperactive-impulsive symptoms and achievement. Trajectory class membership correlated with socio-demographic and diagnostic characteristics, inattention and hyperactive-impulsive symptom trajectories, externalizing behavior in school, and treatment receipt and dosage. Although children with ADHD display substantial heterogeneity in their reading, math, and social skills growth trajectories, those with behavioral and socio-demographic disadvantages are especially likely to display severe levels of academic and social impairment over time. Evidence-based early screening and intervention that directly address academic and social impairments in elementary school-aged children with ADHD are warranted. The ClinicalTrials.gov identifier is NCT00000388.     

On estimation of parameters in latent structure analysis

The latent structure model considered here postulates that a population of individuals can be divided intom classes such that each class is homogeneous in the sense that for the individuals in the class the responses toN dichotomous items or questions are statistically independent. A method is given for deducing the proportions of the population in each latent class and the probabilities of positive responses to each item for individuals in each class from knowledge of the probabilities of positive responses for individuals from the population as a whole. For estimation of the latent parameters on the basis of a sample, it is proposed that the same method of analysis be applied to the observed data. The method has the advantages of avoiding implicitly defined and unobservable quantities, and of using relatively simple computational procedures of conventional matrix algebra, but it has the disadvantages of using only a part of the available information and of using that part asymmetrically.Work supported by the RAND Corporation.     

Pronoun disambiguation: Accessing potential antecedents

Two general classes of pronoun disambiguation processes are considered. In reading “Jack threw a snowball at Phil, but he missed,” both possible antecedents of “he” (“Jack” and “Phil”) may be accessed initially. Or, the actual antecedent alone may be accessed after sufficient semantic context is encoded. To evaluate these alternatives, a yes-no-probe recognition task was used to measure priming of the potential antecedents in sentence comprehension. Subjects read sentences similar to the example and were presented a test word immediately following each sentence. Response times for the actual antecedent (“Jack”) and nonantecedent (“Phil”) probes were obtained. Results indicated that the nonantecedent as well as the antecedent was activated (accessed) in pronoun disambiguation. This conclusion was not affected by the ordering of the antecedent and nonantecedent in the first clause.     

Formulation and Application of the Hierarchical Generalized Random-Situation Random-Weight MIRID

The process-component approach has become quite popular for examining many psychological concepts. A typical example is the model with internal restrictions on item difficulty (MIRID) described by Butter (1994) Butter, R. 1994. Item response models with internal restrictions on item difficulty, Doctoral thesis Leuven, , Belgium: Katholieke Universiteit..  [Google Scholar] and Butter, De Boeck, and Verhelst (1998). This study proposes a hierarchical generalized random-situation random-weight MIRID. The proposed model is more flexible for formulating endogenous latent variables within a multilevel framework, allowing the analysis of polytomous data with complex models (e.g., including item discriminations, random situations, random weights, and heteroskedasticity). The parameters in the proposed model can be estimated using the computer program WinBUGS, which adopts Markov Chain Monte Carlo algorithms. To illustrate the application of the proposed model, a real data set about guilt is analyzed and a comparison of MIRIDs for various conditions is conducted.     

Sentential logics and Maehara Interpolation Property

With each sentential logic C, identified with a structural consequence operation in a sentential language, the class Matr ^* (C) of factorial matrices which validate C is associated. The paper, which is a continuation of [2], concerns the connection between the purely syntactic property imposed on C, referred to as Maehara Interpolation Property (MIP), and three diagrammatic properties of the class Matr* (C): the Amalgamation Property (AP), the (deductive) Filter Extension Property (FEP) and Injections Transferable (IT). The main theorem of the paper (Theorem 2.2) is analogous to the Wroński's result for equational classes of algebras [13]. It reads that for a large class of logics the conjunction of (AP) and (FEP) is equivalent to (IT) and that the latter property is equivalent to (MIP).     

Causal Decision Theory and EPR correlations

The paper argues that on three out of eight possible hypotheses about the EPR experiment we can construct novel and realistic decision problems on which (a) Causal Decision Theory and Evidential Decision Theory conflict (b) Causal Decision Theory and the EPR statistics conflict. We infer that anyone who fully accepts any of these three hypotheses has strong reasons to reject Causal Decision Theory. Finally, we extend the original construction to show that anyone who gives any of the three hypotheses any non-zero credence has strong reasons to reject Causal Decision Theory. However, we concede that no version of the Many Worlds Interpretation (Vaidman, in Zalta, E.N. (ed.), Stanford Encyclopaedia of Philosophy 2014) gives rise to the conflicts that we point out.     

Implementation of global memory models with software that does symbolic computation

A number of software tools are available that do symbolic computation that can facilitate the theoretical analysis of a mathematical model. We made use of one these tools, Mathematica (Wolfram, 1988), to implement the global familiarity memory models of Gillund and Shiffrin (1984) and Murdock (1982, 1983). We describe our implementation, and illustrate the flexibility and efficiency of use that these tools allow.     

Species-specific defense reactions and avoidance learning

Bolles (1970) proposed a theory of avoidance learning, the species-specific defense reaction (SSDR) hypothesis, which emphasized innate constraints on the response repertoire of rats in aversive situations and minimized the role of reinforcement in avoidance learning. The present paper describes Bolles’ (1970, 1971, 1972, 1975, 1978) development of SSDR theory and reviews the empirical tests of its assumptions and predictions. It is concluded that the SSDRs described by Bolles, along with some others, are highly probable in aversive situations but that the response repertoire is not limited to them. Further, there is strong evidence for reinforcement effects in the establishment and maintenance of at least some avoidance responses.