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Validation of a Questionnaire for Personality Profiling using Cognitive Diagnostic Modeling
Abstract
This article describes the development of the ENCUIST (Extroversion, Neuroticism, Callous-Unemotional, Instability, Short-Test) questionnaire, which has been created to provide a personality profiling method based on a cognitive diagnostic modeling framework. The ENCUIST measures the attributes of extroversion, neuroticism, callous unemotionality and overt expressions of anger that are relevant in a forensic context. The scores provided by the ENCUIST are binary classifications of the individuals (high/low) in these attributes. The ENCUIST was developed using a sample of 516 subjects to study its validation through psychometric procedures, including factor analysis, cognitive diagnostic modeling and structural equation modeling. The results supported a four-factor structure. Linear regressions were used to evaluate the predictive validity of the scores provided by ENCUIST with respect to two external criteria that are relevant in the forensic context, namely behavioral activation and behavioral inhibition. The results showed that the extroversion dimension is positively related to behavioral activation, although the effect size is modest and the proportion of explained variance is only 11%. Moreover, the dimensions of neuroticism and anger expression are positively related to behavioral inhibition, with 7% of the variance explained. Together, these results suggest that cognitive diagnostic models are useful tools for the elaboration of personality profiles based on classifying subjects along binary attributes.
... Specifically, current literature includes CDM applications not only in mathematics (e.g., Y.-H. Chen et al., 2019;Tang & Zhan, 2020), reading (e.g., George & Robitzsch, 2021), or foreign language evaluation (e.g., Dong et al., 2021;Du & Ma, 2021), but also for assessing personality (e.g., Huang, 2022;Revuelta et al., 2018), psychological disorders (e.g., de la Torre et al., 2018;Xi et al., 2020) or work and study attitudes (e.g., García et al., 2014;Sorrel et al., 2016). Additionally, CDMs are currently being implemented across heterogeneous conditions (Sessoms & Henson, 2018), with sample sizes as small as 44 (Jang et al., 2015) and up to 71,000 respondents (George & Robitzsch, 2014) , with recent simulation studies supporting the use of parametric CDM methods for sample sizes as small as 100 (e.g., Ma et al., 2022;Ma & Jiang, 2021). ...
Cognitive diagnosis models (CDMs) are used in educational, clinical, or personnel selection settings to classify respondents with respect to discrete attributes, identifying strengths and needs, and thus allowing to provide tailored training/treatment. As in any assessment, an accurate reliability estimation is crucial for valid score interpretations. In this sense, most CDM reliability indices are based on the posterior probabilities of the estimated attribute profiles. These posteriors are traditionally computed using point estimates for the model parameters as approximations to their populational values. If the uncertainty around these parameters is unaccounted for, the posteriors may be overly peaked, deriving into overestimated reliabilities. This article presents a multiple imputation (MI) procedure to integrate out the model parameters in the estimation of the posterior distributions, thus correcting the reliability estimation. A simulation study was conducted to compare the MI procedure with the traditional reliability estimation. Five factors were manipulated: the attribute structure, the CDM model (DINA and G-DINA), test length, sample size, and item quality. Additionally, an illustration using the Examination for the Certificate of Proficiency in English data was analyzed. The effect of sample size was studied by sampling subsets of subjects from the complete data. In both studies, the traditional reliability estimation systematically provided overestimated reliabilities, whereas the MI procedure offered more accurate results. Accordingly, practitioners in small educational or clinical settings should be aware that the reliability estimation using model parameter point estimates may be positively biased. R codes for the MI procedure are made available
... In addition to the application of DCMs to educational and achievement tests, Templin and Henson (2006) proposed a disjunctive version of a DCM, the deterministic input noisy or gate (DINO) model, and applied this model to diagnose the degrees of a psychological gambling disorder. With the exception of their research, most studies have used traditional exploratory clustering methods to classify individuals into different classes in terms of different personality types (e.g., Fals-Stewart et al., 1994;Solomon et al., 2001), and a few studies have applied DCMs to personality assessment (e.g., Revuelta et al., 2018). ...
The forced-choice (FC) item formats used for noncognitive tests typically develop a set of response options that measure different traits and instruct respondents to make judgments among these options in terms of their preference to control the response biases that are commonly observed in normative tests. Diagnostic classification models (DCMs) can provide information regarding the mastery status of test takers on latent discrete variables and are more commonly used for cognitive tests employed in educational settings than for noncognitive tests. The purpose of this study is to develop a new class of DCM for FC items under the higher-order DCM framework to meet the practical demands of simultaneously controlling for response biases and providing diagnostic classification information. By conducting a series of simulations and calibrating the model parameters with a Bayesian estimation, the study shows that, in general, the model parameters can be recovered satisfactorily with the use of long tests and large samples. More attributes improve the precision of the second-order latent trait estimation in a long test, but decrease the classification accuracy and the estimation quality of the structural parameters. When statements are allowed to load on two distinct attributes in paired comparison items, the specific-attribute condition produces better a parameter estimation than the overlap-attribute condition. Finally, an empirical analysis related to work-motivation measures is presented to demonstrate the applications and implications of the new model.
... Up to now, the widely used BIS/BAS scales have been employed in both clinical populations (Claes et al., 2006;Scholten et al., 2006) and healthy individuals (Coplan et al., 2006;Segarra et al., 2007;Jones and Day, 2008). Moreover, the BIS/BAS scales have been used in many countries, such as France (Caci et al., 2007), Poland (Müller and Wytykowska, 2005), Spain (Segarra et al., 2007;Revuelta et al., 2018), and Netherlands (Franken et al., 2005). The scales were shown to possess acceptable reliability and validity in all the above mentioned studies. ...
Objectives: To identify the optimal factor structure of the behavioral inhibition system/behavioral activation system (BIS/BAS) scales and to examine measurement invariance (MI) of the scales across gender among a sample of Chinese undergraduate students.
Methods: Convenience sampling was employed to recruit 1,085 subjects. Participants completed the Chinese version of the BIS/BAS scales. A confirmatory factor analysis (CFA) of competing models was conducted to determine the optimal factor model, followed by a test of MI across gender based on the optimal model.
Results: A single-group CFA indicated that the modified four-factor structure fits best in the total sample. Multiple-group CFAs demonstrated that configural invariance, weak invariance, strong invariance, and strict invariance models of the four-factor structure of the BIS/BAS scales were all acceptable.
Conclusion: The four-factor structure of the Chinese version of the BIS/BAS scales possesses MI across gender.
R package for a set of cognitive diagnosis models. See https://github.com/Wenchao-Ma/GDINA
This paper introduces the R package CDM for cognitive diagnosis models (CDMs). The package implements parameter estimation procedures for two general CDM frameworks , the generalized-deterministic input noisy-and-gate (G-DINA) and the general diagnostic model (GDM). It contains additional functions for analyzing data under these frameworks, like tools for simulating and plotting data, or for evaluating global model and item fit. The paper describes the theoretical aspects of implemented CDM frameworks and it illustrates the usage of the package with empirical data of the common fraction subtraction test by Tatsuoka (1984).
Conventional methods for assessing the validity and reliability of situational judgment test (SJT) scores have proven to be inadequate. For example, factor analysis techniques typically lead to nonsensical solutions, and assumptions underlying Cronbach’s alpha coefficient are violated due to the multidimensional nature of SJTs. In the current article, we describe how cognitive diagnosis models (CDMs) provide a new approach that not only overcomes these limitations but that also offers extra advantages for scoring and better understanding SJTs. The analysis of the Q-matrix specification, model fit, and model parameter estimates provide a greater wealth of information than traditional procedures do. Our proposal is illustrated using data taken from a 23-item SJT that presents situations about student-related issues. Results show that CDMs are useful tools for scoring tests, like SJTs, in which multiple knowledge, skills, abilities, and other characteristics are required to correctly answer the items. SJT classifications were reliable and significantly related to theoretically relevant variables. We conclude that CDM might help toward the exploration of the nature of the constructs underlying SJT, one of the principal challenges in SJT research.
Cognitive diagnostic models (CDM) have been around for more than a decade but their application is far from widespread for mainly two reasons: (1) CDMs are novel, as compared to traditional IRT models. Consequently, many researchers lack familiarity with them and their properties, and (2) Software programs doing CDMs have been expensive and not readily available. The present paper presents a reader-friendly introduction to the CDMs and uses the CDM package (Robitzsch, Kiefer, Cathrice George, & Uenlue, 2014) in R to demonstrate the application of the generalized deterministic-input, noisy-and-gate model (G-DINA; de la Torre, 2011) and interpret the output. R is a free open source tool which can be utilized to conduct a range of CDMs which otherwise would need separate software programs to run each.
In contexts that increasingly demand brief self-report measures (e.g., experience sampling, longitudinal and field studies), researchers seek succinct surveys that maintain reliability and validity. One such measure is the 12-item Brief Aggression Questionnaire (BAQ; Webster et al., 2014), which uses 4 3-item subscales: Physical Aggression, Verbal Aggression, Anger, and Hostility. Although prior work suggests the BAQ's scores are reliable and valid, we addressed some lingering concerns. Across 3 studies (N = 1,279), we found that the BAQ had a 4-factor structure, possessed long-term test-retest reliability across 12 weeks, predicted differences in behavioral aggression over time in a laboratory experiment, generalized to a diverse nonstudent sample, and showed convergent validity with a displaced aggression measure. In addition, the BAQ's 3-item Anger subscale showed convergent validity with a trait anger measure. We discuss the BAQ's potential reliability, validity, limitations, and uses as an efficient measure of aggressive traits.
Background:
Profiling of jobs in terms of competency requirements has increasingly been applied in many organizational settings. Testing these competencies through situational judgment tests (SJTs) leads to validity problems because it is not usually clear which constructs SJTs measure. The primary purpose of this paper is to evaluate whether the application of cognitive diagnosis models (CDM) to competency-based SJTs can ascertain the underlying competencies measured by the items, and whether these competencies can be estimated precisely.
Method:
The generalized deterministic inputs, noisy "and" gate (G-DINA) model was applied to 26 situational judgment items measuring professional competencies based on the great eight model. These items were applied to 485 employees of a Spanish financial company. The fit of the model to the data and the convergent validity between the estimated competencies and personality dimensions were examined.
Results:
The G-DINA showed a good fit to the data and the estimated competency factors, adapting and coping and interacting and presenting were positively related to emotional stability and extraversion, respectively.
Conclusions:
This work indicates that CDM can be a useful tool when measuring professional competencies through SJTs. CDM can clarify the competencies being measured and provide precise estimates of these competencies.
Structural equation modeling (SEM) is a vast field and widely used by many applied researchers in the social and behavioral sciences. Over the years, many software pack-ages for structural equation modeling have been developed, both free and commercial. However, perhaps the best state-of-the-art software packages in this field are still closed-source and/or commercial. The R package lavaan has been developed to provide applied researchers, teachers, and statisticians, a free, fully open-source, but commercial-quality package for latent variable modeling. This paper explains the aims behind the develop-ment of the package, gives an overview of its most important features, and provides some examples to illustrate how lavaan works in practice.
J. A. Gray (1981, 1982) holds that 2 general motivational systems underlie behavior and affect: a behavioral inhibition system (BIS) and a behavioral activation system (BAS). Self-report scales to assess dispositional BIS and BAS sensitivities were created. Scale development (Study 1) and convergent and discriminant validity in the form of correlations with alternative measures are reported (Study 2). In Study 3, a situation in which Ss anticipated a punishment was created. Controlling for initial nervousness, Ss high in BIS sensitivity (assessed earlier) were more nervous than those low in BIS sensitivity. In Study 4, a situation in which Ss anticipated a reward was created. Controlling for initial happiness, Ss high in BAS sensitivity (Reward Responsiveness and Drive scales) were happier than those low in BAS sensitivity. In each case the new scales predicted better than an alternative measure. Discussion is focused on conceptual implications. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The processing of emotional expressions is fundamental for normal socialisation and interaction. Reduced responsiveness to the expressions of sadness and fear has been implicated in the development of psychopathy (R. J. R. Blair, 1995). The current study investigates the sensitivity of children with psychopathic tendencies to facial expressions. Children with psychopathic tendencies and a comparison group, as defined by the Psychopathy Screening Device (PSD; P. J. Frick & R. D. Hare, in press), were presented with a cinematic display of a standardised set of facial expressions that depicted sadness, happiness, anger, disgust, fear, and surprise. Participants observed as these facial expressions slowly evolved through 20 successive frames of increasing intensity. The children with psychopathic tendencies presented with selective impairments; they needed significantly more stages before they could successfully recognise the sad expressions and even when the fearful expressions were at full intensity were significantly more likely to mistake them for another expression. These results are interpreted with reference to an amygdala and empathy impairment explanation of psychopathy.
Hans J. Eysenck and Jeffrey A. Gray have proposed influential theories of the biological bases of personality traits. Eysenck's theory concerns the extraversion, neuroticism and psychoticism traits, whereas Gray proposes the use of new, rotated axes of impulsivity and anxiety. Eysenck uses multiple arousal systems as the central explanatory constructs, whereas Gray describes more specific systems related to behavioural inhibition and activation. This article reviews the evidence relating to these theories provided by studies of c.n.s. and a.n.s. psychophysiology, subjective affect, conditioning and attention and performance. It discusses key predictive successes and failures and methodological problems which may impede theory-testing. It is concluded that there is a solid core of predictive support for the Eysenck theory in some paradigms, such as the moderator effect of stimulation level on individual differences in phasic electrodermal response and eyelid conditioning. In other settings, the theory fails to explain empirical data adequately, especially in studies of subjective response and attention and performance. Gray's theory has advanced research through stimulating interest in moderation of personality effects by motivational variables. It also provides a better explanation than Eysenck's theory for certain data, such as instrumental conditioning to reward stimuli and the positive affectivity of extraverts. Overall, however, Gray's theory explains a narrower range of findings than Eysenck's. There is little evidence that Gray's revised personality axes are generally more predictive of psychophysiological and performance criteria than Eysenck's original dimensions. Finally, it is suggested that the assumptions of the biological approach to personality are in need of reassessment. It is possible that the biological theories may be improved through developments in methodology or through discriminating multiple systems underpinning traits. For example, extraversion may have distinct “reticulo–cortical” and “dopaminergic” aspects. Alternatively, the biological approach may not in fact be adequate for explaining behavioural correlates of traits. In this case, trait research should place more emphasis on cognitive or social bases for personality.
Gray’s revised Reinforcement Sensitivity Theory (rRST; Gray & McNaughton, 2000) may play a role in explaining deficits in Psychoticism (P) and psychopathy (Corr, 2010). In this paper, we examine the relationships of P with anxiety, fear, impulsivity and reward reactivity in normal populations to assess whether these associations mirror the hypothesized role of RST motivations in psychopathy. Two-hundred and twelve participants completed measures of Psychoticism, impulsivity and rRST motivations (BIS-anxiety, FFFS-fear and BAS). BIS-anxiety mediated the association of P with FFFS-fear and BAS-fun seeking. An exploratory factor analysis distinguished between trait impulsivity (P, impulsivity and BIS) and reward reactivity (BAS-reward responsiveness and BAS-drive). Subsequent moderation analyses showed that whilst neither BIS nor BAS moderated the P–impulsivity link, the association between P and impulsivity was more pronounced in individuals with raised levels of FFFS-fear. Findings are discussed in terms of the roles of fear versus anxiety and impulsivity versus reward reactivity in the P–psychopathy continuum.
Taxometric research methods were developed by Paul Meehl and colleagues to distinguish between categorical and dimensional models of latent variables. We have conducted a comprehensive review of published taxometric research that included 177 articles, 311 distinct findings and a combined sample of 533 377 participants. Multilevel logistic regression analyses have examined the methodological and substantive variables associated with taxonic (categorical) findings. Although 38.9% of findings were taxonic, these findings were much less frequent in more recent and methodologically stronger studies, and in those reporting comparative fit indices based on simulated comparison data. When these and other possible confounds were statistically controlled, the true prevalence of taxonic findings was estimated at 14%. The domains of normal personality, mood disorders, anxiety disorders, eating disorders, externalizing disorders, and personality disorders (PDs) other than schizotypal yielded little persuasive evidence of taxa. Promising but still not definitive evidence of psychological taxa was confined to the domains of schizotypy, substance use disorders and autism. This review indicates that most latent variables of interest to psychiatrists and personality and clinical psychologists are dimensional, and that many influential taxonic findings of early taxometric research are likely to be spurious.
To provide an extended assessment of the affective features of psychopathy, Frick developed the Inventory of Callous and Unemotional Traits (ICU), which is a multi-informant questionnaire. Previous studies have provided initial support for the self-report version. The aim of the present study is to investigate the validity of self- as well as other report versions of the ICU and examine associations with measures of psychopathic traits, empathy, antisocial behavior and prosocial attitudes, reward and punishment sensitivity, and personality traits in a Dutch community sample of 455 adolescents (56% males). The results of the present study replicate and extend previous findings on the psychometric properties and the validity of the ICU in a sample of nonreferred youth. The three ICU subscales showed distinctive patterns of associations with key external criteria. Implications and directions for future research are discussed.
Confirmatory factor analysis (CFA) is widely used for examining hypothesized relations among ordinal variables (e.g., Likert-type items). A theoretically appropriate method fits the CFA model to polychoric correlations using either weighted least squares (WLS) or robust WLS. Importantly, this approach assumes that a continuous, normal latent process determines each observed variable. The extent to which violations of this assumption undermine CFA estimation is not well-known. In this article, the authors empirically study this issue using a computer simulation study. The results suggest that estimation of polychoric correlations is robust to modest violations of underlying normality. Further, WLS performed adequately only at the largest sample size but led to substantial estimation difficulties with smaller samples. Finally, robust WLS performed well across all conditions.
Investigators commonly distinguish between primary and secondary psychopathy (H. Cleckley, 1976; D.T. Lykken, 1995), though there is a lack of consensus regarding the best means to achieve this distinction. To address the validity of using R. D. Hare's (2003) Psychopathy Checklist and the G. Welsh (1956) Anxiety Scale for this purpose, the authors used 2 measures of J. A. Gray's (1987) behavioral inhibition system/behavioral activation system (BIS/BAS). Following D. T. Lykken (1995) and D. C. Fowles (1980), the authors hypothesized that primary psychopathy would be associated with a weak BIS and a normal BAS, whereas secondary psychopathy would be associated with a strong BAS and a normal BIS. Results for primary psychopathy were as predicted. Results for secondary psychopathy clearly supported the strong BAS prediction but provided mixed support for the normal BIS prediction.
We propose a general cognitive diagnosis model framework to diagnose mental disorders using item scores obtained from clinical measurement instruments. This framework can be used to validate the extent to which the items measure the specific disorders. The method is illustrated using data obtained with the Dutch version of Millon Clinical Multiaxial Inventory-III.
Self-report measures of emotional expression are common, but their validity to predict objective emotional expression, particularly of anger, is unclear. We tested the validity of the Anger Expression Inventory (AEI; Spielberger et al., 1985 ), Emotional Approach Coping Scale (EAC; Stanton, Kirk, Cameron, & Danoff-Burg, 2000 ), and Toronto Alexithymia Scale-20 (TAS-20; Bagby, Taylor, & Parker, 1994 ) to predict objective anger expression in 95 adults with chronic back pain. Participants attempted to solve a difficult computer maze by following the directions of a confederate who treated them rudely and unjustly. Participants then expressed their feelings for 4 min. Blinded raters coded the videos for anger expression, and a software program analyzed expression transcripts for anger-related words. Analyses related each questionnaire to anger expression. The AEI Anger-Out scale predicted greater anger expression, as expected, but AEI Anger-In did not. The EAC Emotional Processing scale predicted less anger expression, but the EAC Emotional Expression scale was unrelated to anger expression. Finally, the TAS-20 predicted greater anger expression. Findings support the validity of the AEI Anger-Out scale but raise questions about the other measures. The assessment of emotional expression by self-report is complex and perhaps confounded by general emotional experience, the specificity or generality of the emotion(s) assessed, and self-awareness limitations. Performance-based or clinician-rated measures of emotion expression are needed.
This personal historical article traces the development of the Big-Five factor structure, whose growing acceptance by personality researchers has profoundly influenced the scientific study of individual differences. The roots of this taxonomy lie in the lexical hypothesis and the insights of Sir Francis Galton, the prescience of L. L. Thurstone, the legacy of Raymond B. Cattell, and the seminal analyses of Tupes and Christal. Paradoxically, the present popularity of this model owes much to its many critics, each of whom tried to replace it, but failed. In reaction, there have been a number of attempts to assimilate other models into the five-factor structure. Lately, some practical implications of the emerging consensus can be seen in such contexts as personnel selection and classification.
Effortful control is considered to be an important factor in explaining individual differences in trait anger. In the current study, we sought to investigate the relation between anger-primed effortful control (i.e., inhibitory control and error-processing) and trait anger using an affective Go/NoGo task. Individuals low (LTA; n = 45) and high (HTA; n = 49) on trait anger were selected for this study. Behavioral performance (accuracy) and Event-Related Potentials (ERPs; i.e., N2, P3, ERN, Pe) were compared between both groups. Contrary to our predictions, we found no group differences regarding inhibitory control. That is, HTA and LTA individuals made comparable numbers of commission errors on NoGo trials and no significant differences were found on the N2 and P3 amplitudes. With respect to error-processing, we found reduced Pe amplitudes following errors in HTA individuals as compared to LTA individuals, whereas the ERN amplitudes were comparable for both groups. These results indicate that high trait anger individuals show deficits in later stages of error-processing, which may explain the continuation of impulsive behaviours in HTA individuals despite their negative consequences.
In contrast to unidimensional item response models that postulate a single underlying proficiency, cognitive diagnosis models (CDMs) posit multiple, discrete skills or attributes, thus allowing CDMs to provide a finer-grained assessment of examinees' test performance. A common component of CDMs for specifying the attributes required for each item is the Q-matrix. Although construction of Q-matrix is typically performed by domain experts, it nonetheless, to a large extent, remains a subjective process, and misspecifications in the Q-matrix, if left unchecked, can have important practical implications. To address this concern, this paper proposes a discrimination index that can be used with a wide class of CDM subsumed by the generalized deterministic input, noisy "and" gate model to empirically validate the Q-matrix specifications by identifying and replacing misspecified entries in the Q-matrix. The rationale for using the index as the basis for a proposed validation method is provided in the form of mathematical proofs to several relevant lemmas and a theorem. The feasibility of the proposed method was examined using simulated data generated under various conditions. The proposed method is illustrated using fraction subtraction data.
We propose a general cognitive diagnosis model framework to diagnose mental disorders using item scores obtained from clinical measurement instruments. This framework can be used to validate the extent to which the items measure the specific disorders. The method is illustrated using data obtained with the Dutch version of Millon Clinical Multiaxial Inventory-III.
Chapter 1: Introductory Factor Analysis Concepts Chapter 2: Requirements for and Decisions in Choosing Exploratory Common Factor Analysis Chapter 3: Requirements and Decisions for Implementing Exploratory Common Factor Analysis Chapter 4: Factor Analysis Assumptions Chapter 5: Implementing and Interpreting Exploratory Factor Analysis Chapter 6: Summary, Conclusions, and Recommendations
Polytomous attributes, particularly those defined as part of the test development process, can provide additional diagnostic information. The present research proposes the polytomous generalized deterministic inputs, noisy, “and” gate (pG-DINA) model to accommodate such attributes. The pG-DINA model allows input from substantive experts to specify attribute levels and is a general model that subsumes various reduced models. In addition to model formulation, the authors evaluate the viability of the proposed model by examining how well the model parameters can be estimated under various conditions, and compare its classification accuracy against that of the conventional G-DINA model with a modified classification rule. A real-data example is used to illustrate the application of the model in practice.
Cognitive and skills diagnosis models are psychometric models that have immense potential to provide rich information relevant for instruction and learning. However, wider applications of these models have been hampered by their novelty and the lack of commercially available software that can be used to analyze data from this psychometric framework. To address this issue, this article focuses on one tractable and interpretable skills diagnosis model—the DINA model—and presents it didactically. The article also discusses expectation-maximization and Markov chain Monte Carlo algorithms in estimating its model parameters. Finally, analyses of simulated and real data are presented.
This paper introduces a probabilistic approach to the classification and diagnosis of erroneous rules of operations that result from misconceptions ("bugs") in a procedural domain of arithmetic. The model is different from the usual deterministic strategies common in the field of artificial intelligence because variability of response errors is explicitly treated through item response theory. As a concrete example, we analyze a dataset that reflects the use of erroneous rules of operation in problems of signed-number subtraction. The same approach, however, is applicable to the classification of several different groups of response patterns caused by a variety of different underlying misconceptions, different backgrounds of knowledge, or treatment.
The G-DINA (generalized deterministic inputs, noisy “and” gate) model is a generalization of the DINA model with more relaxed assumptions. In its saturated form, the G-DINA model is equivalent
to other general models for cognitive diagnosis based on alternative link functions. When appropriate constraints are applied,
several commonly used cognitive diagnosis models (CDMs) can be shown to be special cases of the general models. In addition
to model formulation, the G-DINA model as a general CDM framework includes a component for item-by-item model estimation based
on design and weight matrices, and a component for item-by-item model comparison based on the Wald test. The paper illustrates
the estimation and application of the G-DINA model as a framework using real and simulated data. It concludes by discussing
several potential implications of and relevant issues concerning the proposed framework.
Keywordscognitive diagnosis–DINA–MMLE–parameter estimation–Wald test–model comparison
This study investigates the ability of psychopathic individuals to process facial emotional expressions. Psychopathic and comparison individuals, as defined by the Hare Psychopathy Checklist Revised (PCL-R), were presented with a standardized set of facial expressions depicting six emotions: happy, surprised, disgusted, angry, sad and fearful. Participants observed as these facial expressions slowly evolved through 20 successive frames of increasing intensity. The dependent variables were latency in responding as measured by frame and number of errors. The psychopathic individuals showed selective impairment for the recognition of fearful expressions. The results are interpreted with reference to the Violence Inhibition Mechanism model of psychopathy and the suggestion that psychopathic individuals present with amygdala dysfunction.
A neuropsychological model of a proposed psychoticism–psychopathy continuum is sketched, which postulates that the core deficits seen both in the personality trait of psychoticism and the clinical condition of psychopathy result from a dysfunction in a behavioural inhibition system (BIS; concerned with detecting and resolving goal-conflicts and associated with the emotion of anxiety) which leads to cognitive inflexibility, inattentiveness and response modulation deficit. Furthermore, differences in activity in a fight-flight-freeze system (FFFS; concerned with avoidance/escape and associated with the emotion of fear) are postulated to differentiate primary (low fearful) and secondary (adequately fearful) psychopaths, with the latter type also experiencing increased activity in a behavioural approach system (BAS; concerned with approach behaviour and associated with the emotion of hopeful anticipation) resulting in dysfunctional impulsiveness. Sub-clinical levels of psychoticism are postulated to result from a defective FFFS and BIS, coupled with an over-active BAS (specifically the fun-seeking, impulsivity facet) – this postulation raises the possibility that psychoticism may be a conflation of these separate influences and may differentiate into two types similar to those found in psychopathy. This model reconciles previously inconsistent findings relating the BIS to psychopathy and points to new avenues of research.
We examined the experience and expression of anger in community samples of 31 maritally violent (MV), 23 maritally dissatisfied-nonviolent (DNV), and 34 maritally satisfied-nonviolent (SNV) men. Two methods were used to assess anger. First, participants completed the State-Trait Anger Expression Inventory (STAXI), which assesses respondents' level of anger experience (State Anger, Trait Anger) and usage of various anger expression styles (Anger In, Anger Out, and Anger Control). Second, participants verbally reported their emotions during a laboratory anger-induction paradigm (Articulated Thoughts in Simulated Situations; ATSS). Results indicated that, relative to DNV and SNV men, MV men scored significantly higher on the STAXI Trait Anger and Anger Out scales, and lower on STAXI Anger Control. MV men articulated a significantly higher number of insulting, demeaning, and belligerent aggressive verbalizations during ATSS anger arousal. Surprisingly, no significant differences were found among the groups in the number of angry verbalizations articulated during ATSS anger arousal. In addition, few relationships were noted between STAXI-assessed anger and ATSS anger verbalizations in MV men. Implications for theories of marital anger and aggression are discussed.
This book reports the results of experiments conducted with normal and psychotic adults, neurotics, and children, in the Institute of Psychiatry (Maudsley and Bethlem Royal Hospitals) at the University of London. The aim is to discover the main dimensions of personality, and to define them operationally.
This paper presents a new class of models for persons-by-items data. The essential new feature of this class is the representation of the persons: every person is represented by its membership tomultiple latent classes, each of which belongs to onelatent classification. The models can be considered as a formalization of the hypothesis that the responses come about in a process that involves the application of a number ofmental operations. Two algorithms for maximum likelihood (ML) and maximum a posteriori (MAP) estimation are described. They both make use of the tractability of the complete data likelihood to maximize the observed data likelihood. Properties of the MAP estimators (i.e., uniqueness and goodness-of-recovery) and the existence of asymptotic standard errors were examined in a simulation study. Then, one of these models is applied to the responses to a set of fraction addition problems. Finally, the models are compared to some related models in the literature.
The purpose of the current paper is to propose a general multicomponent latent trait model (GLTM) for response processes. The proposed model combines the linear logistic latent trait (LLTM) with the multicomponent latent trait model (MLTM). As with both LLTM and MLTM, the general multicomponent latent trait model can be used to (1) test hypotheses about the theoretical variables that underlie response difficulty and (2) estimate parameters that describe test items by basic substantive properties. However, GLTM contains both component outcomes and complexity factors in a single model and may be applied to data that neither LLTM nor MLTM can handle. Joint maximum likelihood estimators are presented for the parameters of GLTM and an application to cognitive test items is described.
Self-regulation is a complex process that involves consumers’ persistence, strength, motivation, and commitment in order to be able to override short-term impulses. In order to be able to pursue their long-term goals, consumers typically need to forgo immediate pleasurable experiences that are detrimental to reach their overarching goals. Although this sometimes involves resisting to simple and small temptations, it is not always easy, since the lure of momentary temptations is pervasive. In addition, consumers’ beliefs play an important role determining strategies and behaviors that consumers consider acceptable to engage in, affecting how they act and plan actions to attain their goals. This dissertation investigates adequacy of some beliefs typically shared by consumers about the appropriate behaviors to exert self-regulation, analyzing to what extent these indeed contribute to the enhancement of consumers’ ability to exert self-regulation.
On both psychological and physiological grounds it is suggested that the hypothesis in Eysenck's theory of introversion-extraversion attributing greater conditionability to the introvert should be replaced by the hypothesis that the introvert is relatively more sensitive to punishment and to frustrative nonreward. The data on which this conclusion is based stem chiefly from the study of eyeblink conditioning in Man as a function of personality, and from the study of the physiological locus of action of the extraverting drug, sodium amobarbital, in animals. It is suggested that the physiological basis of introversion includes, besides the Ascending Reticular Activating System, an inhibitory system comprising the orbital frontal cortex, the medial septal area and the hippocampus. This system is able to carry out the essential psychological functions believed by Eysenck to underlie introversion-extraversion. A new conception of neuroticism as reflecting degree of sensitivity to both reward and punishment is also proposed.
This study investigated the utility of confirmatory factor analysis (CFA) and item response theory (IRT) models for testing the comparability of psychological measurements. Both procedures were used to investigate whether mood ratings collected in Minnesota and China were comparable. Several issues were addressed. The first issue was that of establishing a common measurement scale across groups, which involves full or partial measurement invariance of trait indicators. It is shown that using CFA or IRT models, test items that function differentially as trait indicators across groups need not interfere with comparing examinees on the same trait dimension. Second, the issue of model fit was addressed. It is proposed that person-fit statistics be used to judge the practical fit of IRT models. Finally, topics for future research are suggested.
The related traits of hostility, anger, and aggressiveness have long been suggested as risk factors for coronary heart disease (CHD). Our prior review of this literature (Smith, 1992) found both considerable evidence in support of this hypothesis and important limitations that precluded firm conclusions. In the present review, we discuss recent research on the assessment of these traits, their association with CHD and longevity, and mechanisms possibly underlying the association. In doing so, we illustrate the value of the interpersonal tradition in personality psychology (Sullivan, 1953; Leary, 1957; Carson, 1969; Kiesler, 1996) for not only research on the health consequences of hostility, anger, and aggressiveness, but also for the general study of the effects of emotion, personality and other psychosocial characteristics on physical health.
We discuss the Hypomanic Personality Scale (Hyp; Eckblad & Chapman, 1986) and the Behavioral Inhibition System (BIS-BAS; Carver & White, 1994) and Behavioral Activation System (BAS; Gray, 1991) Scales as risk factors for bipolar disorders. The dysregulation of the BAS is considered to be central and results in higher variability in mood. Therefore, we examined how those scales are associated with mood fluctuations. A total of 59 participants completed a diary for at least 17 days. It included a modified Center for Epidemiologic Studies-Depression Scale (Meyer & Hautzinger, 2001) assessing depression and mania and the Positive and Negative Affect Schedule (Watson, Clark, & Tellegen, 1988). Hyp and BAS predicted levels of mania and of positive affect but also fluctuations of mania. Hyp also predicted instability of negative affect. Our data also suggest that mood variability is a trait-like feature. Both scales seem not to be perfect measures of the dysregulation factor. Future research should assess this dysregulation more directly.
Hostility may contribute to risk for disease through psychosocial vulnerability, including the erosion of the quality of close relationships. This study examined hostility, anger, concurrent ratings of the relationship, and change in marital adjustment over 18 months in 122 married couples. Wives' and husbands' hostility and anger were related to concurrent ratings of marital adjustment and conflict. In prospective analyses, wives' but not husbands' hostility and anger were related to change in marital adjustment. In hierarchical regression and SEM models wives' anger was a unique predictor of both wives' and husbands' change in marital adjustment. The association between wives' anger and change in husbands' marital satisfaction was mediated by husbands' ratings of conflict in the marriage. These results support the role of hostility and anger in the development of psychosocial vulnerability, but also suggest an asymmetry in the effects of wives' and husbands' trait anger and hostility on marital adjustment.
The current paper reviews research suggesting that the presence of a callous and unemotional interpersonal style designates an important subgroup of antisocial and aggressive youth. Specifically, callous-unemotional (CU) traits (e.g., lack of guilt, absence of empathy, callous use of others) seem to be relatively stable across childhood and adolescence and they designate a group of youth with a particularly severe, aggressive, and stable pattern of antisocial behavior. Further, antisocial youth with CU traits show a number of distinct emotional, cognitive, and personality characteristics compared to other antisocial youth. These characteristics of youth with CU traits have important implications for causal models of antisocial and aggressive behavior, for methods used to study antisocial youth, and for assessing and treating antisocial and aggressive behavior in children and adolescents.
CDM: Cognitive diagnostic modeling
- A Robitzsch
- T Kiefer
- A C George
- A Uenlue
Robitzsch A., Kiefer T., George A. C., & Uenlue A. (2017).
CDM: Cognitive diagnostic modeling. R package version
6.0-101. [Computer software]. Retrieved from https://
CRAN.R-project.org/package=CDM
Assessing anger expression: Construct validity of three emotion
- M J Jasisnki
- M A Lumley
- D Latsch
- E Schuster
- E Kinner
- J W Burns
Jasisnki M. J., Lumley M. A., Latsch D., Schuster E.,
Kinner E., & Burns J. W. (2016). Assessing anger
expression: Construct validity of three emotion
Cognitive Diagnostic Modeling and Personality Profiling 13 expression-related measures
Cognitive Diagnostic Modeling and Personality Profiling 13
expression-related measures. Journal of Personality
Assessment, 98, 640-648. https://doi.org/10.1080/0022389