Measurement Invariance of the Internet Addiction Test Among Hong Kong, Japanese, and Malaysian Adolescents

There has been increased research examining the psychometric properties on the Internet Addiction Test across different ages and populations. This population-based study examined the psychometric properties using Confirmatory Factory Analysis and measurement invariance using Item Response Theory (IRT) of the IAT in adolescents from three Asian countries. In the Asian Adolescent Risk Behavior Survey (AARBS), 2,535 secondary school students (55.91% girls) in Grade 7 to Grade 13 (Mean age = 15.61 years; SD=1.56) from Hong Kong (n=844), Japan (n=744), and Malaysia (n=947) completed a survey on their Internet use that incorporated the IAT scale. A nested hierarchy of hypotheses concerning IAT cross-country invariance was tested using multi-group confirmatory factor analysis. Replicating past finding in Hong Kong adolescents, the construct of IAT is best represented by a second-order three-factor structure in Malaysian and Japanese adolescents. Configural, metric, scalar, and partial strict factorial invariance was established across the three samples. No cross-country differences on Internet addiction were detected at latent mean level. This study provided empirical support to the IAT as a reliable and factorially stable instrument, and valid to be used across Asian adolescent populations

Developmental differences in the structure of executive function in middle childhood and adolescence

Although it has been argued that the structure of executive function (EF) may change developmentally, there is little empirical research to examine this view in middle childhood and adolescence. The main objective of this study was to examine developmental changes in the component structure of EF in a large sample (N = 457) of 7–15 year olds. Participants completed batteries of tasks that measured three components of EF: updating working memory (UWM), inhibition, and shifting. Confirmatory factor analysis (CFA) was used to test five alternative models in 7–9 year olds, 10–12 year olds, and 13–15 year olds. The results of CFA showed that a single-factor EF model best explained EF performance in 7–9-year-old and 10–12-year-old groups, namely unitary EF, though this single factor explained different amounts of variance at these two ages. In contrast, a three-factor model that included UWM, inhibition, and shifting best accounted for the data from 13–15 year olds, namely diverse EF. In sum, during middle childhood, putative measures of UWM, inhibition, and shifting may rely on similar underlying cognitive processes. Importantly, our findings suggest that developmental dissociations in these three EF components do not emerge until children transition into adolescence. These findings provided empirical evidence for the development of EF structure which progressed from unity to diversity during middle childhood and adolescence

Thurstonian Scaling of Compositional Questionnaire Data

To prevent response biases, personality questionnaires may use comparative response formats. These include forced choice, where respondents choose among a number of items, and quantitative comparisons, where respondents indicate the extent to which items are preferred to each other. The present article extends Thurstonian modeling of binary choice data (Brown & Maydeu-Olivares, 2011a) to “proportion-of-total” (compositional) formats. Following Aitchison (1982), compositional item data are transformed into log-ratios, conceptualized as differences of latent item utilities. The mean and covariance structure of the log-ratios is modelled using Confirmatory Factor Analysis (CFA), where the item utilities are first-order factors, and personal attributes measured by a questionnaire are second-order factors. A simulation study with two sample sizes, N=300 and N=1000, shows that the method provides very good recovery of true parameters and near-nominal rejection rates. The approach is illustrated with empirical data from N=317 students, comparing model parameters obtained with compositional and Likert scale versions of a Big Five measure. The results show that the proposed model successfully captures the latent structures and person scores on the measured traits

Affective focus increases the concordance between implicit and explicit attitudes

Two attitude dichotomies - implicit versus explicit and affect versus cognition - are presumed to be related. Following a manipulation of attitudinal focus (affective or cognitive), participants completed two implicit measures (Implicit Association Test and the Sorting Paired Features task) and three explicit attitude measures toward cats/dogs (Study 1) and gay/straight people (Study 2). Based on confirmatory factor analysis, both studies showed that explicit attitudes were more related to implicit attitudes in an affective focus than in a cognitive focus. We suggest that, although explicit evaluations can be meaningfully parsed into affective and cognitive components, implicit evaluations are more related to affective than cognitive components of attitudes

Estimation of extended mixed models using latent classes and latent processes: the R package lcmm

The R package lcmm provides a series of functions to estimate statistical models based on linear mixed model theory. It includes the estimation of mixed models and latent class mixed models for Gaussian longitudinal outcomes (hlme), curvilinear and ordinal univariate longitudinal outcomes (lcmm) and curvilinear multivariate outcomes (multlcmm), as well as joint latent class mixed models (Jointlcmm) for a (Gaussian or curvilinear) longitudinal outcome and a time-to-event that can be possibly left-truncated right-censored and defined in a competing setting. Maximum likelihood esimators are obtained using a modified Marquardt algorithm with strict convergence criteria based on the parameters and likelihood stability, and on the negativity of the second derivatives. The package also provides various post-fit functions including goodness-of-fit analyses, classification, plots, predicted trajectories, individual dynamic prediction of the event and predictive accuracy assessment. This paper constitutes a companion paper to the package by introducing each family of models, the estimation technique, some implementation details and giving examples through a dataset on cognitive aging