The measurement of curiosity as a feeling of deprivation

Curiosity as a feeling of deprivation (CFD) reflects feelings of uncertainty and tension that motivate information-seeking and problem-solving behavior. Twenty-seven CFD items were administered to 321 participants (248 women, 73 men) along with other measures of curiosity and other personality traits such as anxiety, anger, and depression. Factor analyses of the CFD items identified 3 factors from which 5-item subscales were developed: (a) a need to feel competent, (b) intolerance experienced when information is inaccessible or inadequate, and (c) a sense of urgency to solve problems. Moderately high correlations of the CFD scales with other measures of curiosity provided evidence of convergent validity, whereas divergent validity was demonstrated by minimal correlations of the CFD scales with the other personality traits.     

Social curiosity and interpersonal perception: a judge x trait interaction

The present study examined the impact of social curiosity on the utilization of social information and the accuracy of personality judgments. In total, 182 individuals who never met each other before were asked to interact for 10 minutes and afterwards to evaluate the personality (Big Five) of their interaction partner. High socially curious judges were more accurate in evaluating the degree of Extraversion and Openness of their interaction partners. Interestingly, high and low curious judges differed significantly in the utilization of verbal and nonverbal cues displayed by their interaction partner. Specifically, high socially curious judges more often used valid cues for inferring Extraversion and Openness. No differences in interpersonal accuracy and cue utilization were found for Neuroticism, Conscientiousness, and Agreeableness. The results suggest that high socially curious individuals are more accurate in judging visible traits and that this higher accuracy is grounded in a more comprehensive utilization of valid cues.     

A taxometric analysis of the latent structure of psychopathy: evidence for dimensionality

The taxonomic status of psychopathy is controversial. Whereas some studies have found evidence that psychopathy, at least its antisocial component, is distributed as a taxon, others have found that both major components of psychopathy-callousness/unemotionality and impulsivity/antisocial behavior-appear to distribute as dimensions and show little evidence of taxonicity. In the present study, recent advances in taxometric analysis were added to P. Meehl's (1995) multiple consistency tests strategy for assessing taxonicity, and they were applied to Psychopathy Checklist-Revised (R. D. Hare, 2003) ratings of 4,865 offenders sampled from multiple forensic settings. The results indicated that both the individual components of psychopathy and their interface are distributed dimensionally. Both the implications of these results for research in psychopathy and the integration of these findings with previous taxometric studies of psychopathy are discussed.     

Multicomponent latent trait models for ability tests

A major research direction for ability measurement has been to identify the information-processes that are involved in solving test items through mathematical modeling of item difficulty. However, this research has had limited impact on ability measurement, since person parameters are not included in the process models. The current paper presents some multicomponent latent trait models for reproducing test performance from both item and person parameters on processing components. Components are identified from item subtasks, in which performance is a logistic function (i.e., Rasch model) of person and item parameters, and then are combined according to a mathematical model of processing on the composite item.The author would like to thank David Thissen for his invaluable insights concerning this model and an anonymous reviewer for his suggestion about the sample space for the model.This research was partially supported by National Institute of Education grant number NIE-6-7-0156 to Susan E. Whitely, principal investigator. However the opinions expressed herein do not necessarily reflect the position or policy of the National Institute of Education, and no official endorsement by the National Institute of Education should be referred. Part of this paper was presented at the annual meeting of thePsychometric Society, Monterey, California: June, 1979.     

Higher-order latent trait models for cognitive diagnosis

Higher-order latent traits are proposed for specifying the joint distribution of binary attributes in models for cognitive diagnosis. This approach results in a parsimonious model for the joint distribution of a high-dimensional attribute vector that is natural in many situations when specific cognitive information is sought but a less informative item response model would be a reasonable alternative. This approach stems from viewing the attributes as the specific knowledge required for examination performance, and modeling these attributes as arising from a broadly-defined latent trait resembling theϑ of item response models. In this way a relatively simple model for the joint distribution of the attributes results, which is based on a plausible model for the relationship between general aptitude and specific knowledge. Markov chain Monte Carlo algorithms for parameter estimation are given for selected response distributions, and simulation results are presented to examine the performance of the algorithm as well as the sensitivity of classification to model misspecification. An analysis of fraction subtraction data is provided as an example. This research was funded by National Institute of Health grant R01 CA81068. We would like to thank William Stout and Sarah Hartz for many useful discussions, three anonymous reviewers for helpful comments and suggestions, and Kikumi Tatsuoka and Curtis Tatsuoka for generously sharing data.     

Curiosity adapted the cat: the role of trait curiosity in newcomer adaptation

Using longitudinal data from 123 newcomers across 12 telemarketing organizations, we examined the role of 2 forms of trait curiosity (specific and diversive) as antecedents of proximal adaptation behaviors (information seeking and positive framing) and more distal, in-role and extra-role behaviors (job performance and taking charge). Results suggest that specific curiosity predicts information seeking behaviors, whereas diversive curiosity promotes positive framing. Results also support the relationship between positive framing and performance and the extra-role behavior of taking charge. Overall, the study validates the role of curiosity as a multifaceted individual difference that serves as an antecedent to newcomer adaptation.     

Sufficient statistics and latent trait models

For questionnaires with two answer categories, it has been proven in complete generality that if a minimal sufficient statistic exists for the individual parameter and if it is the same statistic for all values of the item parameters, then the raw score (or the number of correct answers) is the minimal sufficient statistic. It follows that the model must by of the Rasch type with logistic item characteristic curves and equal item-discriminating powers.This paper extends these results to multiple choice questionnaires. It is shown that the minimal sufficient statistic for the individual parameter is a function of the so-called score vector. It is also shown that the so-called equidistant scoring is the only scoring of a questionnaire that allows for a real valued sufficient statistic that is independent of the item parameters, if a certain ordering property for the sufficient statistic holds.     

A taxometric study of the latent structure of disgust sensitivity: converging evidence for dimensionality

Disgust sensitivity has recently been implicated as a specific vulnerability factor for several anxiety-related disorders. However, it is not clear whether disgust sensitivity is a dimensional or categorical phenomenon. The present study examined the latent structure of disgust by applying three taxometric procedures (maximum eigenvalue, mean above minus below a cut, and latent-mode factor analysis) to data collected from 2 large nonclinical samples on 2 different measures of disgust sensitivity. Disgust sensitivity in the first sample (n=1,153) was operationalized by disgust reactions to food, animals, body products, sex, body envelope violations, death, hygiene, and sympathetic magic, as assessed by the Disgust Sensitivity Scale (J. Haidt, C. McCauley, & P. Rozin, 1994). Disgust Sensitivity Scale indicators of core, animal reminder, and contamination disgust were also examined in the 1st sample. Disgust sensitivity in the 2nd independent sample (n=1,318) was operationalized by disgust reactions to animals, injections and blood draws, mutilation and death, rotting foods, and odors, as assessed by the Disgust Emotion Scale (R. A. Kleinknecht, E. E. Kleinknecht, & R. M. Thorndike, 1997). Results across both samples provide converging evidence that disgust sensitivity is best conceptualized as a dimensional construct, present to a greater or lesser extent in all individuals. These findings are discussed in relation to the conceptualization and assessment of disgust sensitivity as a specific dimensional vulnerability for certain anxiety and related disorders.     

The curiosity and exploration inventory-II: Development, factor structure, and psychometrics

Given curiosity’s fundamental role in motivation, learning, and well-being, we sought to refine the measurement of trait curiosity with an improved version of the Curiosity and Exploration Inventory (CEI; [Kashdan, T. B., Rose, P., & Fincham, F. D. (2004). Curiosity and exploration: Facilitating positive subjective experiences and personal growth opportunities. Journal of Personality Assessment, 82, 291–305]). A preliminary pool of 36 items was administered to 311 undergraduate students, who also completed measures of emotion, emotion regulation, personality, and well-being. Factor analyses indicated a two-factor model—motivation to seek out knowledge and new experiences (Stretching; five items) and a willingness to embrace the novel, uncertain, and unpredictable nature of everyday life (Embracing; five items). In two additional samples (ns = 150 and 119), we cross-validated this factor structure and provided initial evidence for construct validity. This includes positive correlations with personal growth, openness to experience, autonomy, purpose in life, self-acceptance, psychological flexibility, positive affect, and positive social relations, among others. Applying item response theory (IRT) to these samples (n = 578), we showed that the items have good discrimination and a desirable breadth of difficulty. The item information functions and test information function were centered near zero, indicating that the scale assesses the mid-range of the latent curiosity trait most reliably. The findings thus far provide good evidence for the psychometric properties of the 10-item CEI-II.     

A nonparametric approach for assessing latent trait unidimensionality

Assuming a nonparametric family of item response theory models, a theory-based procedure for testing the hypothesis of unidimensionality of the latent space is proposed. The asymptotic distribution of the test statistic is derived assuming unidimensionality, thereby establishing an asymptotically valid statistical test of the unidimensionality of the latent trait. Based upon a new notion of dimensionality, the test is shown to have asymptotic power 1. A 6300 trial Monte Carlo study using published item parameter estimates of widely used standardized tests indicates conservative adherence to the nominal level of significance and statistical power averaging 81 out of 100 rejections for examinee sample sizes and psychological test lengths often incurred in practice.The referees' comments were remarkably detailed and greatly enhanced the writeup and sensitized the author to certain pertinent issues. Discussions with Fritz Drasgow, Lloyd Humphreys, Dennis Jennings, Brian Junker, Robert Linn, Ratna Nandakumar, and Robin Shealy were also very useful.This research was supported by the Office of Naval Research under grant N00014-84-K-0186; NR 150-533, and by the National Science Foundation under grant DMS 85-03321.     

The asymptotic posterior normality of the latent trait for polytomous IRT models

Chang and Stout (1993) presented a derivation of the asymptotic posterior normality of the latent trait given examinee responses under nonrestrictive nonparametric assumptions for dichotomous IRT models. This paper presents an extention of their results to polytomous IRT models in a fairly straightforward manner. In addition, a global information function is defined, and the relationship between the global information function and the currently used information functions is discussed. An information index that combines both the global and local information is proposed for adaptive testing applications.This research was partially supported by Educational Testing Service Allocation Project No. 79424. The author wishes to thank Charles Davis, Xuming He, Frank Jenkins, Spence Swinton, William Stout, Ming-Mai Wang, and Zhiliang Ying for their helpful comments and discussions. The author particularly wishes to thank the Editor, Shizuhiko Nishisato, the Associate Editor, and three anonymous reviewers for their thoroughness and thoughtful suggestions.     

A general latent trait model for response processes

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.This research was partially supported by the National Institute of Education grant number NIE-6-7-0156 to Susan Embretson (Whitely), principal investigator. However the optinions expressed herein do not necessarily reflect the position or policy of the National Institute of Education, and no official endorsement by the National Institute of Education should be inferred.     

A latent trait model for dichotomous choice data

The PARELLA model is a probabilistic parallelogram model that can be used for the measurement of latent attitudes or latent preferences. The data analyzed are the dichotomous responses of persons to stimuli, with a one (zero) indicating agreement (disagreement) with the content of the stimulus. The model provides a unidimensional representation of persons and items. The response probabilities are a function of the distance between person and stimulus: the smaller the distance, the larger the probability that a person will agree with the content of the stimulus. An estimation procedure based on expectation maximization and marginal maximum likelihood is developed and the quality of the resulting parameter estimates evaluated.I gratefully acknowledge Ivo Molenaar and Wijbrandt van Schuur for their advice and encouragement during the course of the investigation, Derk-Jan Kiewiet who constructed the program for the ML estimator for the person parameter and Anne Boomsma, Wendy Post, Tom Snijders, and David Thissen for their comments on smaller aspects of the investigation.     

The NEO Five-Factor Inventory: latent structure and relationships with dimensions of anxiety and depressive disorders in a large clinical sample

The present study evaluated the latent structure of the NEO Five-Factor Inventory (NEO FFI) and relations between the five-factor model (FFM) of personality and dimensions of DSM-IV anxiety and depressive disorders (panic disorder, generalized anxiety disorder [GAD], obsessive-compulsive disorder, social phobia [SOC], major depressive disorder [MDD]) in a large sample of outpatients (N = 1,980). Exploratory structural equation modeling (ESEM) was used to show that a five-factor solution provided acceptable model fit, albeit with some poorly functioning items. Neuroticism demonstrated significant positive associations with all but one of the disorder constructs whereas Extraversion was inversely related to SOC and MDD. Conscientiousness was inversely related to MDD but demonstrated a positive relationship with GAD. Results are discussed in regard to potential revisions to the NEO FFI, the evaluation of other NEO instruments using ESEM, and clinical implications of structural paths between FFM domains and specific emotional disorders.     

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.     

A multidimensional latent trait model for measuring learning and change

A latent trait model is presented for the repeated measurement of ability based on a multidimensional conceptualization of the change process. A simplex structure is postulated to link item performance under a given measurement condition or occasion to initial ability and to one or more modifiabilities that represent individual differences in change. Since item discriminations are constrained to be equal within a measurement condition, the model belongs to the family of multidimensional Rasch models. Maximum likelihood estimators of the item parameters and abilities are derived, and an example provided that shows good recovery of both item and ability parameters. Properties of the model are explored, particularly for several classical issues in measuring change.     

The latent structure of occupations

Triads of occupations were given to 1300 high-school pupils of both sexes in order to find the affinities of the occupations and the values they used to arrive at the affinities. The values used to perceive occupations come from the subject; nevertheless they could be categorized into a scheme of 20 different values, with the residue category containing less than 1% of the answers. In accordance with previous research in this field, an almost universal structure of occupations was found. The following variables had no influence on the choice of occupational affinities: age, trend of study, SES, father's occupation, mother's occupation, vocational maturity, and preferred occupation. Only the pupils of one school were significantly different in affiliating the occupations in the triads. Furthermore, girls perceive the world of occupations more uniformly than boys.Underlying this universal structure of occupations there exists a latent structure, specific to each individual, which explains why the world of occupations is seen in the way it is. This latent structure of occupations is influenced by the individual's specific background.     

States of curiosity and interest enhance memory differently in adolescents and in children

Curiosity – broadly defined as the desire to acquire new information – enhances learning and memory in adults. In addition, interest in the information (i.e., when the information is processed) can also facilitate later memory. To date, it is not known how states of pre‐information curiosity and post‐information interest enhance memory in childhood and adolescence. We used a trivia paradigm in which children and adolescents (N = 60, 10–14 years) encoded trivia questions and answers associated with high or low curiosity. States of high pre‐answer curiosity enhanced later memory for trivia answers in both children and adolescents. However, higher positive post‐answer interest enhanced memory for trivia answers beyond the effects of curiosity more strongly in adolescents than in children. These results suggest that curiosity and interest have positive effects on learning and memory in childhood and adolescence, but might need to be harnessed in differential ways across child development to optimize learning.