Using SAS PROC CALIS to fit Level-1 error covariance structures of latent growth models

In the present article, we demonstrates the use of SAS PROC CALIS to fit various types of Level-1 error covariance structures of latent growth models (LGM). Advantages of the SEM approach, on which PROC CALIS is based, include the capabilities of modeling the change over time for latent constructs, measured by multiple indicators; embedding LGM into a larger latent variable model; incorporating measurement models for latent predictors; and better assessing model fit and the flexibility in specifying error covariance structures. The strength of PROC CALIS is always accompanied with technical coding work, which needs to be specifically addressed. We provide a tutorial on the SAS syntax for modeling the growth of a manifest variable and the growth of a latent construct, focusing the documentation on the specification of Level-1 error covariance structures. Illustrations are conducted with the data generated from two given latent growth models. The coding provided is helpful when the growth model has been well determined and the Level-1 error covariance structure is to be identified.     

Studying group and time invariance in maximal reliability for multiple‐component measuring instruments via covariance structure modelling

A method for examining invariance in maximal reliability for weighted combinations of congeneric measures is described. The approach is developed within the framework of covariance structure modelling and allows one to ascertain whether a multi‐component instrument consisting of homogeneous measures is associated with the same minimal relative error variance in distinct populations or over time. The procedure yields as a by‐product an interval measure of discrepancy in maximal reliability across independent groups or assessment occasions, and is illustrated with two examples.     

Examining time‐invariance in reliability in multi‐wave,multi‐indicator models: A covariance structure analysis approach accounting for indicator specificity

A covariance structure analysis method for testing time‐invariance in reliability in multiwave, multiple‐indicator models in outlined. The approach accounts for observed variable specificity and permits, in addition, estimation of reliability in terms of ‘pure’ measurement error variance. The proposed procedure is developed within a confirmatory factor analysis framework and illustrated with data from a cognitive intervention study.     

General mixture item response models with different item response structures: Exposition with an application to Likert scales

This article proposes a general mixture item response theory (IRT) framework that allows for classes of persons to differ with respect to the type of processes underlying the item responses. Through the use of mixture models, nonnested IRT models with different structures can be estimated for different classes, and class membership can be estimated for each person in the sample. If researchers are able to provide competing measurement models, this mixture IRT framework may help them deal with some violations of measurement invariance. To illustrate this approach, we consider a two-class mixture model, where a person’s responses to Likert-scale items containing a neutral middle category are either modeled using a generalized partial credit model, or through an IRTree model. In the first model, the middle category (“neither agree nor disagree”) is taken to be qualitatively similar to the other categories, and is taken to provide information about the person’s endorsement. In the second model, the middle category is taken to be qualitatively different and to reflect a nonresponse choice, which is modeled using an additional latent variable that captures a person’s willingness to respond. The mixture model is studied using simulation studies and is applied to an empirical example.     

On the chi‐square approximation to the exact distribution of goodness‐of‐fit statistics in multinomial models with composite hypotheses

Multinomial models are increasingly being used in psychology, and this use always requires estimating model parameters and testing goodness of fit with a composite null hypothesis. Goodness of fit is customarily tested with recourse to the asymptotic approximation to the distribution of the statistics. An assessment of the quality of this approximation requires a comparison with the exact distribution, but how to compute this exact distribution when parameters are estimated from the data appears never to have been defined precisely. The main goal of this paper is to compare two different approaches to defining this exact distribution. One of the approaches uses the marginal distribution and is, therefore, independent of the data; the other approach uses the conditional distribution of the statistics given the estimated parameters and, therefore, is data—dependent. We carried out a thorough study involving various parameter estimation methods and goodness‐of‐fit statistics, all of them members of the general class of power‐divergence measures. Included in the study were multinomial models with three to five cells and up to three parameters. Our results indicate that the asymptotic distribution is rarely a good approximation to the exact marginal distribution of the statistics, whereas it is a good approximation to the exact conditional distribution only when the vector of expected frequencies is interior to the sample space of the multinomial distribution.     

Using latent class growth analysis to form trajectories of premorbid adjustment in schizophrenia

Premorbid adjustment varies widely among individuals with schizophrenia and has been shown to bear significantly on prodrome and onset characteristics, and on cognition, symptoms, and functioning after onset. The current analysis focused on the Premorbid Adjustment Scale, a retrospective measure assessing social and academic function at several time points from early childhood to illness onset. In an effort to explore discrete developmental subtypes, we applied latent class growth analysis to data from the Premorbid Adjustment Scale in our sample of individuals with schizophrenia (N = 208), finding three latent trajectory classes. The first of these classes showed consistently adequate-to-good social and academic functioning before onset; the second showed initially good function and deterioration with time until onset; the third showed poor functioning in childhood that deteriorated further during the years up to diagnosis. The classes differed significantly in terms of age of onset, processing speed, and functioning after onset. There were no significant differences in symptomatology. Our findings illustrate a potentially powerful methodological approach to the problem of heterogeneity in schizophrenia research, and add weight to the notion that aspects of premorbid history may be useful for subtyping schizophrenia patients. The potential implications of this subtyping strategy, including those pertaining to potential genetics studies, are discussed.     

Using Dynamic Panel Models to Study Age‐related Differences and Time‐related Changes in Personality

Along with an increasing interest in the plasticity and role of personality across the adult lifespan comes the need for a diverse set of innovative statistical approaches to study it. With this paper, we set out to illustrate some of the possibilities and challenges in modelling age‐related differences and time‐related changes in personality psychology by means of dynamic panel models. To this end, we first distinguish between the study of age‐related differences and time‐related changes and demonstrate how the treatment of age and time as either discrete or continuous variables implies important modelling choices. Second, we present a selection of four example cases that address the topic of age moderation in diverse matters and with different objectives. Based on our cross‐tabulation of age and time as discrete and continuous variables, the first two example cases represent fairly well‐established models (cases A and B), whereas the remaining cases are used to illustrate current developments in the field (cases C and D). We close the paper with some final remarks on current limitation and future research directions. © 2019 European Association of Personality Psychology     

The impact of a peer counselling scheme to address bullying in an all‐girl London secondary school: A short‐term longitudinal study

Background A variety of peer support schemes are now widely used in schools, notably to reduce bullying. However, there has been little systematic investigation of the impact and effectiveness of these approaches. Aims To assess the impact of a peer counselling scheme on peer counsellors and the school community. Sample The research was conducted in a North London all‐girls state secondary school. Data were collected from all lower school classes (years 7, 8, and 9) and some staff members, in addition to year 10 peer counsellors and an age equivalent comparison group. Method A detailed 1‐year longitudinal study combined qualitative and quantitative methods of assessment. Results Peer counsellors benefited from their involvement through an acquisition of transferable communication and interpersonal skills, and, compared to age‐matched control pupils, had increased social self‐esteem. There were no reductions in self‐reported bullying and victimization, but in general pupils believed that there was less bullying in school and that the school was doing more about bullying, with year 7 students showing the most positive changes. Conclusions Peer‐counselling schemes can improve self‐esteem of peer supporters, and also impact positively on perceptions of bullying in the school; but impact on actual experiences of bullying is less clear, and there may be problems with the acceptance and use of such programmes by older students.     

Using unexpected questions to elicit information and cues to deceit in interpreter‐based interviews

We examined whether speech‐related differences between truth tellers and liars are more profound when answering unexpected questions than when answering expected questions. We also examined whether the presence of an interpreter affected these results. In the experiment, 204 participants from the United States (Hispanic participants only), Russia, and the Republic of Korea were interviewed in their native language by a native‐speaking interviewer or by a British interviewer through an interpreter. Truth tellers discussed a trip that they had made during the last 12 months; liars fabricated a story about such a trip. The key dependent variables were the amount of information provided and the proportion of all statements that were complications. The proportion of complications distinguished truth tellers from liars better when answering unexpected than expected questions, but only in interpreter‐absent interviews. The number of details provided did not differ between truth tellers and liars or between interpreter‐absent and interpreter‐present interviews.     

Bayesian analysis of mixtures in structural equation models with non‐ignorable missing data

Structural equation models (SEMs) have become widely used to determine the interrelationships between latent and observed variables in social, psychological, and behavioural sciences. As heterogeneous data are very common in practical research in these fields, the analysis of mixture models has received a lot of attention in the literature. An important issue in the analysis of mixture SEMs is the presence of missing data, in particular of data missing with a non‐ignorable mechanism. However, only a limited amount of work has been done in analysing mixture SEMs with non‐ignorable missing data. The main objective of this paper is to develop a Bayesian approach for analysing mixture SEMs with an unknown number of components and non‐ignorable missing data. A simulation study shows that Bayesian estimates obtained by the proposed Markov chain Monte Carlo methods are accurate and the Bayes factor computed via a path sampling procedure is useful for identifying the correct number of components, selecting an appropriate missingness mechanism, and investigating various effects of latent variables in the mixture SEMs. A real data set on a study of job satisfaction is used to demonstrate the methodology.     

Experience with visual barriers and its effects on subsequent gaze‐following in 12‐ to 13‐month‐olds

Thirty 12‐ to 13‐month‐olds were tested to determine whether they could use the self as an analogy for understanding others' looking. Using a procedure similar to Brooks and Meltzoff (2002) , we examined gaze‐following when the adult's view of a target was occluded by a blindfold (blindfold without training). Some infants received experience with the blindfold's sight‐blocking qualities (blindfold with training). The control was a headband condition. Gaze‐following was highest in the headband condition. Gaze‐following in the headband and blindfold without training conditions, but not the blindfold with training conditions, were significantly greater than zero. These results demonstrate that 12‐ to 13‐month‐olds have some understanding of the looking behaviour of others. Only weak support was found for simulation theories of the development of social cognition.     

Using segmented linear regression models with unknown change points to analyze strategy shifts in cognitive tasks

Some years ago, Beem (1993, 1995) described a program for fitting two regression lines with an unknown change point (Segcurve). He suggested that such models are useful for the analysis of a variety of phenomena and gave an example of an application to the study of strategy shifts in a mental rotation task. This technique has also proven to be very fruitful for investigating strategy use and strategy shifts in other cognitive tasks. Recently, Beem (1999) developed SegcurvN, which fitsn regression lines with (n - 1) unknown change points. In the present article we present this new technique and demonstrate the usefulness of a three-phase segmented linear regression model for the identification of strategies and strategy shifts in cognitive tasks by applying it to data from a numerosity judgment experiment. The advantages and shortcomings of this technique are evaluated.     

Gender differences on the Five to Fifteen questionnaire in a non‐referred sample with inattention and hyperactivity‐impulsivity and a clinic‐referred sample with hyperkinetic disorder

Lambek, R., Trillingsgaard, A., Kadesjö, B., Damm, D. & Thomsen, P. H. (2010). Gender differences on the Five to Fifteen questionnaire in a non‐referred sample with inattention and hyperactivity‐impulsivity and a clinic‐referred sample with hyperkinetic disorder. Scandinavian Journal of Psychology 51, 540–447. The aim of the present study was to examine gender differences in children with inattention, hyperactivity, and impulsivity on the Five to Fifteen (FTF) parent questionnaire. First, non‐referred girls (n = 43) and boys (n = 51) with problems of attention and hyperactivity‐impulsivity and then clinic‐referred girls (n = 35) and boys (n = 66) with hyperkinetic disorder (HKD) were compared on the FTF. Results suggested that non‐referred boys were more hyperactive‐impulsive than non‐referred girls, whereas clinic‐referred boys and girl with HKD were more similar than dissimilar on the FTF questionnaire. Secondly, it was examined whether the application of gender mixed norms versus gender specific norms would result in varying proportions of clinic‐referred children with HKD being identified as impaired on the subdomains of the FTF questionnaire. Based on results it was concluded that the use of a gender mixed normative sample may lead to overestimation of impairment in boys with HKD, but the type of sample applied to define impairment on the FTF should depend on the purpose for applying the questionnaire.     

Computer aided self‐monitoring to increase academic production and reduce self‐injurious behavior in a child with autism

Self‐monitoring to increase the on‐task behavior of students with learning disabilities has been the focus of numerous studies in the literature. This study examined the effectiveness of computer aided self‐monitoring of academic task completion to reduce self‐injurious behavior in a 13‐year‐old male student with autism. Using an ABAB design, data were collected over 22 sessions in a resource‐reading classroom. Visual and statistical analyses indicated that when self‐monitoring of activity completion was implemented, rates of completion increased and maladaptive behaviors such as self‐injurious behavior and tantruming decreased. Discussion follows for implications for self‐monitoring with students with autism. Copyright © 2009 John Wiley & Sons, Ltd.     

Haptics in learning to read with children from low socio‐economic status families

This study assessed the effects of multi‐sensory training on the understanding of the alphabetic principle in kindergarten children from low socio‐economic status families. Two interventions were compared, called HVAM (visual and haptic exploration of letters) and VAM (visual exploration of letters). The interventions were conducted by either researchers or teachers. Results showed that performance in the letter recognition task and in the initial phoneme identification task were higher after HVAM training than after VAM training in kindergarten. Moreover, pseudo‐word decoding scores improved more after HVAM training than after VAM training in first grade. This delayed effect on decoding was explained by the children's poor performance on some language skills necessary for reading acquisition. Visuo‐haptic exploration enables the children first to increase performance on letter knowledge and initial phoneme awareness and then allowed better decoding skills. No differences were found between the interventions conducted by researchers and those conducted by teachers.     

Fixed‐links models for investigating experimental effects combined with processing strategies in repeated measures designs: A cognitive task as example

Fixed‐links models enable the investigation of experimental effects in combination with processing strategies in the framework of repeated measures designs. The consideration of different processing strategies is reasonable whenever the task requirements can be met in different ways. Effects due to specific processing strategies become obvious in comparing the models representing these processing strategies and also by investigating the variances of the corresponding latent variables. The usefulness of such models is demonstrated by the reaction time data of a cognitive task including three treatment levels. Two different processing strategies were considered: analytic and holistic. The results indicated that the participants applied both processing strategies. The analytic strategy was primarily applied for performing with respect to the second and third treatment levels and the holistic strategy with respect to the first treatment level.     

Name‐changes in post‐war France: The traumatic experiences of the Shoah and its consequences on the second and third generation with reference to the example of name‐changes

Starting from our collective initiative to work on the theme of ‘The strength of the name’, which has given rise both to a conference as well as a documentary called: And their name, they have changed it, I have sought to draw attention in this article to the difference between proper names, patronymic names, and the so‐called Name‐of‐the‐father. Pronouncing names involves designating the languages of names, which also refer to the accents of names, since I have proposed the idea that each name is evocative of a language, and that changing it also modifies the language of the name. I have approached the question of the name by considering cases of name‐changes, essential with regard to Ashkenazi Jewish families who changed their name after the Shoah, along with the trauma that numerous Jewish families suffered after the war. French jurisprudence does not permit reversion to the original name, once it has been changed to a more French‐sounding name, owing to the immutability of the name and the foreign sound of the names of origin.     

Sensitivity to differences between enjoyment and non‐enjoyment smiles in children with autism spectrum disorder

The sensitivity of male children (5–15 years) with and without autism spectrum disorder (ASD) to the affective state of others was tested using an emotion recognition task. Only children without ASD could reliably differentiate between enjoyment and non‐enjoyment smiles. Results are considered in terms of the social impairments of children with ASD.     

Proneness to hallucinations and delusions in a non‐clinical sample: Exploring associations with metacognition and negative affect

Commonly, individuals prone to hallucinations and delusions hold dysfunctional metacognitive beliefs and report higher levels of negative affect, yet, these associations have not been clearly investigated in non‐clinical samples due to the failure to control for high intercorrelations between variables. The aim of the current study was to investigate how hallucination and delusion proneness are associated with dysfunctional metacognitions and negative affect. A cross‐sectional sample of 715 students free from psychiatric diagnoses (M_age = 28.1 years, SD = 10.9, range 18–65) completed the Launay‐Slade Hallucination Scale (LSHS‐R); Peters et al. Delusion Inventory (PDI‐21); Depression, Anxiety, and Stress Scale (DASS‐21); and the Metacognition Questionnaire (MCQ‐30). Findings that participants who were prone to both hallucinations and delusions reported elevated levels of negative affect support the need for targeted mental health treatment for individuals who experience psychological distress related to their hallucinatory and delusional experiences. While metacognition beliefs of need to control thoughts and cognitive self‐consciousness, along with the anxiety and stress DASS‐21 subscales appeared as significant cross‐sectional predictors of proneness to hallucinations and delusions, only metacognitions demonstrated any notable predictive value for delusion proneness. This finding questions the role of metacognitions in determining hallucination and delusion proneness in non‐clinical samples.