The Longitudinal Psychometric Properties of the EAS Temperament Survey in Adolescence

Studies on the psychometric properties of the EAS Temperament Survey (EAS) have produced equivocal results. In particular the psychometrics of the EAS are largely unknown in adolescence. Confirmatory factor analysis was used to explore the EAS structure in adolescents. Structural equation modeling was also used to assess measurement invariance and factor stability. A modified 4-factor model provided the best fit to the data and demonstrated reasonable longitudinal invariance and stability. Furthermore, the standardized factor scores correlated at near unity with the sum of observed scores, suggesting factor interpretations remained unchanged. However, the modifications suggest that further work is necessary.     

The Emotionality Activity Sociability Temperament Survey: Factor analysis and temporal stability in a longitudinal cohort

We investigated Buss and Plomin’s Emotionality Activity Sociability (EAS) Temperament Survey for Children, used to assess temperament. Temperament is believed to comprise stable traits that change little over time. We examined stability of EAS temperament in the Avon Longitudinal Study of Parents and Children, in which 7429 mothers completed the EAS when their children were 3, 5 and 6 years old. Factor analysis was conducted at each time point, and stability over time was assessed using correlation and mixed effects regression modelling, accounting for differences within and between individuals. A four-factor model provided the best fit, with 19–20 of the 20 items loading onto the dimensions predicted by Buss and Plomin. Test–retest correlations ranged from 0.52–0.64 (3–5 years), 0.59–0.74 (5–6 years) and 0.46–0.58 (3–6 years). Mixed effects regression modelling suggested good stability over time: differences between, rather than within, individuals accounted for between 69% and 82% of the variance. This study demonstrates the stability of temperament over time, a vital pre-requisite to investigating childhood temperament as a predictor of outcomes.     

Depression Anxiety Stress Scales-21: Factor Structure and Test-Retest Invariance,and Temporal Stability and Uniqueness of Latent Factors in Older Adults

This study examined the factor structure and test-retest invariance, and temporal stability and uniqueness of the latent factors (depression, anxiety, and stress) of the Depression Anxiety Stress Scales-21 (DASS-21; Lovibond & Lovibond, 1995) in group a of 269 older adults (age ranging from 60 to 85 years) from the general community. Participants completed the DASS-21 twice, 3 months apart. Confirmatory factor analysis (CFA) of their ratings at Time 1 indicated support for the original 3-factor oblique model (factors for depression, anxiety, and stress). Additional analyses showed support for test-retest invariance for both the measurement (configural, metric and thresholds) and structural (variances and covariances) components of this model. Results also indicated temporal stability and uniqueness of the latent factors. The practical, theoretical, research and clinical implications of the findings are discussed.     

Temperament and Happiness in Children

The relation between temperament and happiness was assessed in 311 children aged 9–12. Parents rated their children’s temperament using the Emotionality, Activity, and Sociability Temperament Survey (EAS) and rated their children’s happiness. Children rated their own temperament using the EAS and the Piers–Harris Self Concept Scale for Children Second Edition, and they rated their own happiness using a single-item measure, the Oxford Happiness Questionnaire Short Form, and the Subjective Happiness Scale. Parents’ and children’s temperament ratings conformed to the four factor structure proposed by Buss and Plomin(Temperament: Early developing personality traits, Lawrence Erlbaum Associates, Hillsdale, 1984) supporting the use of children’s self-reports as an additional measure of temperament. Temperament accounted for between 9 and 29% of the variance in children’s happiness depending on the measures. Children who were more social and active, and less shy, emotional, and anxious were happier. These results parallel the well-established relation between happiness and personality in adults; temperament traits akin to extraversion (Sociability) were positively associated with happiness whereas traits akin to neuroticism (Emotionality) were negatively associated with happiness. Additionally, children who were rated higher in the temperament trait Activity were happier.     

On the Relation Between the Linear Factor Model and the Latent Profile Model

The relationship between linear factor models and latent profile models is addressed within the context of maximum likelihood estimation based on the joint distribution of the manifest variables. Although the two models are well known to imply equivalent covariance decompositions, in general they do not yield equivalent estimates of the unconditional covariances. In particular, a 2-class latent profile model with Gaussian components underestimates the observed covariances but not the variances, when the data are consistent with a unidimensional Gaussian factor model. In explanation of this phenomenon we provide some results relating the unconditional covariances to the goodness of fit of the latent profile model, and to its excess multivariate kurtosis. The analysis also leads to some useful parameter restrictions related to symmetry.     

Implications of Indeterminate Factor-Error Covariances for Factor Construction, Prediction, and Determinacy

The assumptions of the model for factor analysis do not exclude a class of indeterminate covariances between factors and error variables (Grayson, 2003). The construction of all factors of the model for factor analysis is generalized to incorporate indeterminate factor-error covariances. A necessary and sufficient condition is given for indeterminate factor-error covariances to be arbitrarily small, for mean square convergence of the regression predictor of factor scores, and for the existence of a unique determinate factor and error variable. The determinate factor and error variable are uncorrelated and satisfy the defining assumptions of factor analysis. Several examples are given to illustrate the results. Requests for reprints should be sent to Wim P. Krijnen, Lisdodde 1, 9679 MC Scheemda, The Netherlands.     

Decomposing person and occasion-specific effects: an extension of latent state-trait (LSI) theory to hierarchical LST models

An extension of latent state-trait (LST) theory to hierarchical LST models is presented. In hierarchical LST models, the covariances between 2 or more latent traits are explained by a general 3rd-order factor, and the covariances between latent state residuals pertaining to different traits measured on the same measurement occasion are explained by 2nd-order latent occasion-specific factors. Analogous to recent developments in multitrait-multimethod methodology, all factors are interpreted in relation to factors taken as comparison standards. An empirical example from test anxiety research illustrates how estimates of additive variance components due to general trait, specific trait, occasion, state residual, method, and measurement error can be obtained using confirmatory factor analysis. Advantages and limitations of these models are discussed.     

Six-month stability of individual differences in sports coaches’ burnout,self-compassion and social support

Using a three-wave prospective cross-lagged panel design, the study examined six-month stability of burnout, self-compassion and social support among sports coaches in terms of measurement invariance, mean-level change, rank-order stability, and structural stability. The participating coaches (N = 422; M_age = 44.48, SD = 11.03) completed an online questionnaire measuring self-compassion, social support, coach burnout and demographics at baseline and two follow-ups at three months and six months. The various forms of stability were assessed using structural equation modeling. There was no significant mean-level change in burnout, self-compassion, or social support, and all three constructs exhibited measurement invariance. Rank-order stability remained relatively high, ranging from 0.78 to 0.94 across the three time points. For all three constructs, covariances between latent factors were invariant over time, indicating high structural stability. While self-compassion and social support were positively related, both were negatively related to coach burnout. These results confirm the importance of preventing and addressing symptoms of burnout, low self-compassion and poor social support in sports settings.     

The Development of Latent Dimensions of Psychopathology across Early Childhood: Stability of Dimensions and Moderators of Change

Recent research has described the structure of psychopathology as including one general and multiple specific factors, and this structure has been found in samples across development. However, little work has examined whether this structure is consistent across time, particularly in young children, within the same sample. Further, few studies have examined factors that influence the magnitude of the stability of latent dimensions of psychopathology. In the present study, we examine these issues in a community sample of 545 children assessed at ages 3 and 6. In addition, we explored child temperament, parental history of psychopathology, and parenting behaviors as potential moderators of the longitudinal stability of latent dimensions of psychopathology. We found that the same bifactor model structure identified at age 3 provided an adequate fit to the data at age 6. Further, our model revealed significant homotypic stability of the general, internalizing, and externalizing specific factors. We also found evidence of differentiation of psychopathology over time with the general factor at age 3 predicting the externalizing factor at age 6. However, we failed to identify moderators of the longitudinal associations between psychopathology latent factors. Overall, our results bolster support for the bifactor structure of psychopathology, particularly in early childhood.     

Temperament and Happiness in Children in India

The relation between temperament and happiness was assessed in a sample of 441 children aged 7–14 years drawn from a population in Northern India. Parents assessed their children’s happiness and rated their children’s temperament using the Emotionality, Activity, and Sociability Temperament Survey (EAS). Children self-reported their own happiness using a single-item measure, the Oxford Happiness Scale Short Form, and the Subjective Happiness Scale. Parents’ temperament ratings conformed to the four factor structure proposed by Buss and Plomin (Temperament: early developing personality traits. Lawrence Erlbaum Associates, Hillsdale, 1984): Emotionality, Activity, Sociability, and Shyness. Temperament accounted for between 4 and 11% of the variance in children’s happiness depending on the measures. Children who were more social and active, and less shy, were happier. This result parallels the well-established relation between happiness and personality in adults and is similar to recent research on happiness and temperament in children; temperament traits akin to extraversion were positively associated with happiness. However, despite that neuroticism and its temperament counterpart are strongly and consistently linked to happiness in adults, the relation between happiness and the temperament trait associated with neuroticism (i.e., Emotionality) was weak. This suggests that the relations between temperament and happiness in children may not completely generalize across cultures.     

The Stability of Temperament from Early Childhood to Early Adolescence:A Multi‐method,Multi‐informant Examination

Temperament is a core aspect of children's psychological functioning and is assumed to be at least somewhat stable across childhood. However, little research has assessed the stability of temperament from early childhood to early adolescence. Moreover, few studies have examined the influence of measurement and analytic methods on the stability of early temperament over periods of more than a few years. We obtained laboratory observations and mother and father reports of temperamental negative and positive emotionality and effortful control from 559 three‐year‐olds. Approximately nine years later, children and both parents completed questionnaire measures of similar temperament constructs. Zero‐order correlations revealed greater within‐informant than cross‐informant stability. In addition, compared with parent reports, early childhood laboratory measures showed greater convergent and divergent validity with child, mother, and father reports at age 12. Finally, latent temperament variables at age 3 composed of laboratory and parent‐report measures and latent variables at age 12 composed of parent and child reports showed moderate stability. There was also a weak but significant association of early effortful control with later negative and positive emotionality. Results have implications for assessing temperament and knowledge of the stability of temperament across childhood. Copyright © 2018 European Association of Personality Psychology     

Using Latent Class Analysis to Model Temperament Types

Mixture models are appropriate for data that arise from a set of qualitatively different subpopulations. In this study, latent class analysis was applied to observational data from a laboratory assessment of infant temperament at four months of age. The EM algorithm was used to fit the models, and the Bayesian method of posterior predictive checks was used for model selection. Results show at least three types of infant temperament, with patterns consistent with those identified by previous researchers who classified the infants using a theoretically based system. Multiple imputation of group memberships is proposed as an alternative to assigning subjects to the latent class with maximum posterior probability in order to reflect variance due to uncertainty in the parameter estimation. Latent class membership at four months of age predicted longitudinal outcomes at four years of age. The example illustrates issues relevant to all mixture models, including estimation, multi-modality, model selection, and comparisons based on the latent group indicators.     

Conditional covariance structure of generalized compensatory multidimensional items

Some nonparametric dimensionality assessment procedures, such as DIMTEST and DETECT, use nonparametric estimates of item pair conditional covariances given an appropriately chosen subtest score as their basic building blocks. Such conditional covariances given some subtest score can be regarded as an approximation to the conditional covariances given an appropriately chosen unidimensional latent composite, where the composite is oriented in the multidimensional test space direction in which the subtest score measures best. In this paper, the structure and properties of such item pair conditional covariances given a unidimensional latent composite are thoroughly investigated, assuming a semiparametric IRT modeling framework called a generalized compensatory model. It is shown that such conditional covariances are highly informative about the multidimensionality structure of a test. The theory developed here is very useful in establishing properties of dimensionality assessment procedures, current and yet to be developed, that are based upon estimating such conditional covariances.In particular, the new theory is used to justify the DIMTEST procedure. Because of the importance of conditional covariance estimation, a new bias reducing approach is presented. A byproduct of likely independent importance beyond the study of conditional covariances is a rigorous score information based definition of an item's and a score's direction of best measurement in the multidimensional test space.This paper is based on a chapter of the first author's doctoral dissertation, written at the University of Illinois and supervised by the second author. Part of this research has been presented at the annual meeting of the National Council on Measurement in Education, San Francisco, April 1995.The authors would like to thank Jeff Douglas, Xuming He and Ming-mei Wang for their comments and suggestions. The research of the first author was partially supported by an ETS/GREB Psychometric Fellowship, and by Educational Testing Service Research Allocation Project 884-01. The research of the second author was partially supported by NSF grant DMS 97-04474.     

A Prospective Longitudinal Study of Shyness from Infancy to Adolescence: Stability, Age-Related Changes, and Prediction of Socio-Emotional Functioning

This longitudinal, population-based and prospective study investigated the stability, age-related changes, and socio-emotional outcomes of shyness from infancy to early adolescence. A sample of 921 children was followed from ages 1.5 to 12.5?years. Parent-reported shyness was assessed at five time points and maternal- and self-reported social skills and symptoms of anxiety and depression were assessed at age 12.5?years. Piecewise latent growth curve analysis was applied, with outcomes regressed on latent shyness intercept and slope factors. Results showed moderate stability and increasing levels of shyness across time, with more variance and a steeper increase in early as compared to mid-to-late childhood. Both stable shyness and increased shyness in mid-to-late (but not early) childhood predicted poorer social skills and higher levels of anxiety and depression symptoms in early adolescence. The implications of the evidence for two developmental periods in shyness trajectories with differential impact on later socio-emotional functioning are discussed.     

Correlations of multiple rider behaviors with self-reported attitudes,perspectives on traffic rule strictness and social desirability

Powered Two-Wheeler (PTW) riders constitute a very vulnerable group of road users, while riding a PTW is considerably more dangerous than using any other motor vehicle. Behavioral issues have been identified major moderating factors to PTW crashes, as riders display great variability in their attitudes towards road safety. Τhe aim of this paper is to present a thorough, overarching structure of relationships correlating various unsafe stated PTW rider behaviors (riding after alcohol consumption, speeding, helmet use and texting) with several self-reported attitude parameters and factors regarding rider perspectives on traffic rule strictness and social desirability. A structural equation model (SEM) was developed using data from the ESRA2 survey, which provided a broad sample encompassing 5,958 respondent riders from 32 countries. Numerous statistical relationships were discovered and quantified correlating the four examined unsafe rider behaviors with eight latent unobserved variables. All covariances between unsafe behaviors were found to be positive and statistically significant, indicating that a rider who will engage more frequently in every single one of the four examined unsafe riding behaviors is more likely to also engage in all the others as well.     

Stability and Invariance of Psychopathic Traits from Late Adolescence to Young Adulthood

The current study examined the longitudinal stability and invariance of psychopathic traits in a large community sample of male twins from ages 17 to 23. Participants were assessed across 6 years to gauge the stability and measurement invariance of the Minnesota Temperament Inventory (MTI), a Cleckley-based measure of psychopathic personality traits, and how family functioning and externalizing behavior were linked to these traits. A latent variable approach was used to model the structure of the MTI and provide a statistical test of measurement invariance across time. The results revealed support for invariance and moderate to strong stability of the MTI factors, which showed significant associations with the external correlates in late adolescence but not early adulthood.     

Stability of language in childhood: a multiage, multidomain, multimeasure, and multisource study

The stability of language across childhood is traditionally assessed by exploring longitudinal relations between individual language measures. However, language encompasses many domains and varies with different sources (child speech, parental report, experimenter assessment). This study evaluated individual variation in multiple age-appropriate measures of child language derived from multiple sources and stability between their latent variables in 192 young children across more than 2 years. Structural equation modeling demonstrated the loading of multiple measures of child language from different sources on single latent variables of language at ages 20 months and 48 months. A large stability coefficient (r = .84) obtained between the 2 language latent variables. This stability obtained even when accounting for family socioeconomic status, maternal verbal intelligence, education, speech, tendency to respond in a socially desirable fashion, and child social competence. Stability was also equivalent for children in diverse childcare situations and for girls and boys. Across age, from the beginning of language acquisition to just before school entry, aggregating multiple age-appropriate methods and measures at each age and multiple reporters, children show a strong stability of individual differences in general language development.     

The Houdini Transformation: True,but Illusory

Molenaar (2003, 2011) showed that a common factor model could be transformed into an equivalent model without factors, involving only observed variables and residual errors. He called this invertible transformation the Houdini transformation. His derivation involved concepts from time series and state space theory. This article verifies the Houdini transformation on a general latent variable model using algebraic methods. The results show that the Houdini transformation is illusory in the sense that the Houdini-transformed model remains a latent variable model. Contrary to common knowledge, a model that is a path model with only observed variables and residual errors may, in fact, be a latent variable model.     

Estimating, testing, and comparing specific effects in structural equation models: the phantom model approach

The phantom model approach for estimating, testing, and comparing specific effects within structural equation models (SEMs) is presented. The rationale underlying this novel method consists in representing the specific effect to be assessed as a total effect within a separate latent variable model, the phantom model that is added to the main model. The following favorable features characterize the method: (a) It enables the estimation, testing, and comparison of arbitrary specific effects for recursive and nonrecursive models with latent and manifest variables; (b) it enables the bootstrapping of confidence intervals; and (c) it can be applied with all standard SEM programs permitting latent variables, the specification of equality constraints, and the bootstrapping of total effects. These features along with the fact that no manipulation of matrices and formulas is required make the approach particularly suitable for applied researchers. The method is illustrated by means of 3 examples with real data sets.