Latent variable models for multivariate longitudinal ordinal responses

The paper proposes a full information maximum likelihood estimation method for modelling multivariate longitudinal ordinal variables. Two latent variable models are proposed that account for dependencies among items within time and between time. One model fits item‐specific random effects which account for the between time points correlations and the second model uses a common factor. The relationships between the time‐dependent latent variables are modelled with a non‐stationary autoregressive model. The proposed models are fitted to a real data set.     

Expected consequences of anger‐related behaviours

In a study with 140 participants (66 men, 74 women), we investigated behaviour outcome expectancies (cognitive, affective and relational) regarding a broad group of anger‐related behaviours (e.g. hit someone, run away). Results of a three‐mode component analysis indicated that behaviour outcome expectancies vary considerably, depending on the behaviour (aggressive versus nonaggressive ones), the consequence (consequences related to the self versus consequences for the anger) and the individual. The findings are discussed in the context of catharsis theory, emotion regulation and functionalistic accounts of emotion‐related behaviour. Copyright © 2006 John Wiley & Sons, Ltd.     

Latent variable models for analyzing children's processing ability

In this paper, we develop a latent processing ability model to analyze the speed of processing ability data. Our approach can not only effectively evaluate the effects of covariates on the latent processing ability, but also estimate the latent trait of each child by calculating its posterior mean. In addition, we derive the correlations structure of latent traits among different age groups. Simulations are conducted to evaluate the performance of our proposed model. The results indicated that the estimation of model parameters is satisfactory overall. The method is evaluated using real data from children aged 4–7 years in Changchun, China.     

Latent trait models and dichotomization of graded responses

This paper discusses thecompatibility of the polychotomous Rasch model with dichotomization of the response continuum. It is argued that in the case of graded responses, the response categories presented to the subject are essentially an arbitrary polychotomization of the response continuum, ranging for example from total rejection or disagreement to total acceptance or agreement of an item or statement. Because of this arbitrariness, the measurement outcome should be independent of the specific polychotomization applied, for example, presenting a specific multicategory response format should not affect the measurement outcome. When such is the case, the original polychotomous model is called compatible with dichotomization.A distinction is made between polychotomization or dichotomization before the fact, that is, in constructing the response format, and polycho- or dichotomization after the fact, for example in dichotomizing existing graded response data.It is shown that, at least in case of dichotomization after-the-fact, the polychotomous Rasch model is not compatible with dichotomization, unless a rather special condition of the model parameters is met. Insofar as it may be argued that dichotomization before the fact is not essentially different from dichotomization after the fact, the value of the unidimensional polychotomous Rasch model is consequently questionable. The impact of our conclusion on related models is also discussed.     

Latent variable models for the measurement of flashbulb memories: a comparative approach

Flashbulb memories are defined as vivid, long‐lasting, and detailed memories for the circumstances in which people learned of shocking and important public events, that is the so‐called reception context (Brown & Kulik, 1977). They are considered as highly integrated cores of autobiographical knowledge which aggregate attributes of the reception context (Conway, 1995). The present paper deals with the measurement of flashbulb memories. Data from both a correlational and an experimental study were submitted to confirmatory factor analysis, latent trait model, and latent class model (LCM) procedures. Results confirmed that the clustered nature of flashbulb memories is better assessed by a LCM. The attribute of mass media as a source of the original news seemed to be crucial in defining flashbulb memories. The impact of the mass media was discussed, in that flashbulb memories appear to be not indelible and immune to forgetting. Copyright © 2004 John Wiley & Sons, Ltd.     

Generalized latent variable models with non‐linear effects

Until recently, item response models such as the factor analysis model for metric responses, the two‐parameter logistic model for binary responses and the multinomial model for nominal responses considered only the main effects of latent variables without allowing for interaction or polynomial latent variable effects. However, non‐linear relationships among the latent variables might be necessary in real applications. Methods for fitting models with non‐linear latent terms have been developed mainly under the structural equation modelling approach. In this paper, we consider a latent variable model framework for mixed responses (metric and categorical) that allows inclusion of both non‐linear latent and covariate effects. The model parameters are estimated using full maximum likelihood based on a hybrid integration–maximization algorithm. Finally, a method for obtaining factor scores based on multiple imputation is proposed here for the non‐linear model.     

Confidence in work‐related goals and feelings of exhaustion during a therapeutic intervention for burnout: A time‐series approach

This study investigated recursive relations between confidence in achieving work‐related goals and work exhaustion among employees who participated in an intervention to reduce their burnout. Thirty‐six employees of age 33–59 years suffering from severe burnout (28 females and 8 males) filled in burnout and well‐being measures before and after a 10‐month therapeutic intervention. They also filled in weekly measures of confidence in work‐related goals (progress and capability) and work exhaustion throughout the intervention, as well as 4 weeks before and 4 weeks afterwards. Intra‐individual variation was modelled using dynamic factor analyses. The results showed that, for most participants, confidence in work‐related goals and work exhaustion during a given week could be predicted from those of the preceding week. Moreover, high self‐esteem predicted low weekly stability in goal confidence, whereas high burnout contributed to high weekly stability in work exhaustion. The intra‐individual stabilities in goal confidence and exhaustion also predicted which of the participants benefited from the intervention in terms of increasing well‐being and decreasing work‐related stress.     

Hostility‐ and gender‐related differences in oscillatory responses to emotional facial expressions

Hostility is associated with biases in the perception of emotional facial expressions, such that ambiguous or neutral expressions tend to be perceived as threatening or angry. In this study, the effects of hostility and gender on the perception of angry, neutral, and happy faces and on the oscillatory dynamics of cortical responses elicited by these presentations were investigated using time–frequency decomposition by means of wavelet transforms. Feelings of hostility predisposed subjects to perceive happy and neutral faces as less friendly. This effect was more pronounced in women. In hostile subjects, presentation of emotional facial expressions also evoked stronger posterior synchronization in the theta and diminished desynchronization in the alpha band. This may signify a prevalence of emotional responding over cognitive processing. These effects were also more pronounced in females. Hostile females, but not hostile males, additionally showed a widespread synchronization in the alpha band. This synchronization is tentatively explained as a manifestation of inhibitory control which is present in aggressive females, but not in aggressive males. Aggr. Behav. 35:502–513, 2009. © 2009 Wiley‐Liss, Inc.     

On the explaining‐away phenomenon in multivariate latent variable models

Many probabilistic models for psychological and educational measurements contain latent variables. Well‐known examples are factor analysis, item response theory, and latent class model families. We discuss what is referred to as the ‘explaining‐away’ phenomenon in the context of such latent variable models. This phenomenon can occur when multiple latent variables are related to the same observed variable, and can elicit seemingly counterintuitive conditional dependencies between latent variables given observed variables. We illustrate the implications of explaining away for a number of well‐known latent variable models by using both theoretical and real data examples.     

Bayesian latent variable models for the analysis of experimental psychology data

In this paper, we address the use of Bayesian factor analysis and structural equation models to draw inferences from experimental psychology data. While such application is non-standard, the models are generally useful for the unified analysis of multivariate data that stem from, e.g., subjects’ responses to multiple experimental stimuli. We first review the models and the parameter identification issues inherent in the models. We then provide details on model estimation via JAGS and on Bayes factor estimation. Finally, we use the models to re-analyze experimental data on risky choice, comparing the approach to simpler, alternative methods.     

Behavioral and emotional responses to diet‐related support and control among same‐sex couples

Members of 63 lesbian and 72 gay couples reported how frequently their partners engaged in diet‐related social support and control (persuasion and pressure) and how they responded behaviorally and emotionally to such attempts. Although lesbian women received more frequent diet‐related social support than gay men, there were no gender differences in the receipt of diet‐related social control. Results of multilevel models that controlled for body mass index revealed that all participants responded to all types of involvement with guilt and to support and persuasion with appreciation. Responses to pressure differed for lesbian women and gay men and acted as a function of relationship quality. Findings from this study may increase awareness of the importance of same‐sex partners' involvement in eating behaviors.     

Model‐related factor score predictors for confirmatory factor analysis

The present paper introduces model‐related (MR) factor score predictors, which reflect specific aspects of confirmatory factor models. The development is mainly based on Schönemann and Steiger's regression score components, but it can also be applied to the factor score coefficients. It is shown that the rotation of factor score predictors has no impact on the covariance matrix reproduced from the corresponding regression component patterns. Thus, regression score components or factor score coefficients can be rotated in order to obtain the required properties. This idea is the basis for MR factor score predictors, which are computed by means of a partial Procrustes rotation towards a target pattern representing the interesting properties of a confirmatory factor model. Two examples demonstrate the construction of MR factor score predictors reflecting specific constraints of a factor model.     

Bayesian analysis of structural equation models with mixed exponential family and ordered categorical data

Structural equation models are very popular for studying relationships among observed and latent variables. However, the existing theory and computer packages are developed mainly under the assumption of normality, and hence cannot be satisfactorily applied to non‐normal and ordered categorical data that are common in behavioural, social and psychological research. In this paper, we develop a Bayesian approach to the analysis of structural equation models in which the manifest variables are ordered categorical and/or from an exponential family. In this framework, models with a mixture of binomial, ordered categorical and normal variables can be analysed. Bayesian estimates of the unknown parameters are obtained by a computational procedure that combines the Gibbs sampler and the Metropolis–Hastings algorithm. Some goodness‐of‐fit statistics are proposed to evaluate the fit of the posited model. The methodology is illustrated by results obtained from a simulation study and analysis of a real data set about non‐adherence of hypertension patients in a medical treatment scheme.     

Latent class models for testing monotonicity and invariant item ordering for polytomous items

Two assumptions that are relevant to many applications using item response theory are the assumptions of monotonicity (M) and invariant item ordering (IIO). A latent class model is proposed for ordinal items with inequality constraints on the class-specific item means. This model is used as a tool for testing for violations of M and IIO. A Gibbs sampling scheme is used for estimating the model parameters. It is shown that the deviance information criterion can be used as an overall test of M and IIO, while posterior predictive checks can be used to test these assumptions at the item level. A real data application illustrates a model-fitting strategy for detecting items that violate M and IIO.     

Dual identity,in‐group projection,and out‐group feelings among ethnic minority groups

This study extends research on dual identity and in‐group projection by considering category prototypicality and indispensability, and by focusing on ethnic minority members and their attitudes towards the native majority and minority out‐groups. Among a sample of 491 participants of the three largest immigrant‐origin groups in the Netherlands, it was found that the minority in‐group was seen as relatively more prototypical and relatively more indispensable for the national category in comparison with minority out‐groups, but not in comparison with the native majority. In support of the in‐group projection model, stronger dual identity was associated with higher relative in‐group prototypicality and relative in‐group indispensability in comparison with the majority and, via both these relative perceptions, to a less positive attitude towards the native Dutch. In addition and in support of the common in‐group identity model, dual identity was associated with more positive minority out‐group feelings via higher minority out‐group prototypicality and indispensability. It is concluded that dual identity can have both positive and negative consequences for intergroup relations depending on perceived (relative) prototypicality and indispensability, and depending on whether the out‐group is the majority or other minorities.     

individual and work‐related factors influencing burnout of mental health professionals: a meta‐analysis

The current study identifies and assesses individual and work‐related factors as correlates of burnout among mental health professionals. Results of a meta‐analysis indicate that age and work setting variables are the most significant indicators of emotional exhaustion and depersonalization. In terms of level of personal accomplishment, the age and work hours variables were the most significant indicators with positive correlations. On the basis of these results, the authors seek to determine resources that can assist with developing programs for preventing and treating burnout syndromes of mental health professionals.