We review common situations in Bayesian latent variable models where the prior distribution that a researcher specifies differs from the prior distribution used during estimation. These situations can arise from the positive definite requirement on correlation matrices, from sign indeterminacy of factor loadings, and from order constraints on…

This study used a meta-analytic structural equation modeling approach to build extended versions of the simple view of reading (SVR) model in second and foreign language (SFL) learning contexts (i.e., SVR-SFL). Based on the correlation coefficients derived from primary studies, we replicated and integrated two previous extended meta-analytic SVR…

In the last decade, research on the connection between curiosity and creativity has surged revealing a positive correlation. However, these findings are primarily based on cross-sectional studies, which do not establish the direction of the relationship between creativity and curiosity. Is curiosity the driving force behind creativity, or does…

In the context of Bayesian factor analysis, it is possible to compute plausible values, which might be used as covariates or predictors or to provide individual scores for the Bayesian latent variables. Previous simulation studies ascertained the validity of mean plausible values by the mean squared difference of the mean plausible values and the…

This study examined the impact of omitting covariates interaction effect on parameter estimates in multilevel multiple-indicator multiple-cause models as well as the sensitivity of fit indices to model misspecification when the between-level, within-level, or cross-level interaction effect was left out in the models. The parameter estimates…

Small sample sizes pose a severe threat to convergence and accuracy of between-group level parameter estimates in multilevel structural equation modeling (SEM). However, in certain situations, such as pilot studies or when populations are inherently small, increasing samples sizes is not feasible. As a remedy, we propose a two-stage regularized…

Many applications of structural equation modeling involve ordinal (e.g., Likert) variables. A popular way of dealing with ordinal variables is to estimate the model with polychoric correlations rather than Pearson correlations. Such an estimation also requires the asymptotic covariance matrix of polychoric correlations. It is computationally…

We present a method for Bayesian structural equation modeling of sample correlation matrices as correlation structures. The method transforms the sample correlation matrix to an unbounded vector using the matrix logarithm function. Bayesian inference about the unbounded vector is performed assuming a multivariate-normal likelihood, with a mean…

This study investigates the relations between school readiness and self-regulation skills of preschool children and parental involvement towards education of their preschool children. More specifically, we focused on the mediation role of preschoolers' self-regulation skills on the relation between parental involvement and school readiness. The…

Given the recent attention to language-domain-specific grit in the field of SLA and the scarcity of research on the antecedents of L2 grit, we proposed a model that links L2 learners' basic psychological needs (BPN) (i.e. autonomy, competence, and relatedness), L2 grit (i.e. perseverance of effort (PE) and consistency of interest (CI)), and L2…

Accounting for model misspecification in Bayesian structural equation models is an active area of research. We present a uniquely Bayesian approach to misspecification that models the degree of misspecification as a parameter--a parameter akin to the correlation root mean squared residual. The misspecification parameter can be interpreted on its…

The objective of this study is to ascertain the relative influences and predictive relationships between metacognitive listening strategies, critical listening attitudes and academic listening skills of Turkish teacher candidates. In consideration of the ease of accessibility and economic factors, the participants were selected through the…

Conceptually, although the effectiveness of communication is generally associated with the development of language skills, studies that model this relationship comprehensively are limited. Based on this, the current study examines the relationship between different linguistic variables (listening skills, attitude towards reading habits, speech…

Effect modification (EM) may cause bias in network meta-analysis (NMA). Existing population adjustment NMA methods use individual patient data to adjust for EM but disregard available subgroup information from aggregated data in the evidence network. Additionally, these methods often rely on the shared effect modification (SEM) assumption. In this…

This study aimed to investigate the relationships among computational thinking (CT) skills, science, technology, engineering and mathematics (STEM) attitude, and thinking styles with the help of structural equation modeling and to determine to what extent the variables of STEM attitude and thinking styles explained CT skills. The study, conducted…