A full structural equation model (SEM) typically consists of both a measurement model (describing relationships between latent variables and observed scale items) and a structural model (describing relationships among latent variables). However, often researchers are primarily interested in testing hypotheses related to the structural model while…

Common ways to test associations between two repeatedly measured constructs have two primary limitations. Studies often report the average effects and ignore the heterogeneity. Independently interpreted autoregression and cross-lagged coefficients (i.e. local effects) may not match the holistic dynamic patterns (i.e. considering all coefficients…

Although generalizability theory (GT) designs typically are analyzed using analysis of variance (ANOVA) procedures, they also can be integrated into structural equation models (SEMs). In this tutorial, we review basic concepts for conducting univariate and multivariate GT analyses and demonstrate advantages of doing such analyses within SEM…

The logistic and confined exponential curves are frequently used in studies of growth and learning. These models, which are nonlinear in their parameters, can be estimated using structural equation modeling software. This paper proposes a single combined model, a weighted combination of both models. Mplus, Proc Calis, and lavaan code for the model…

In the past decade, moderated mediation analysis has been extensively and increasingly employed in social and behavioral sciences. With its widespread use, it is particularly important to ensure the moderated mediation analysis will not bring spurious results. Spurious effects have been studied in both mediation and moderation analysis, but this…

Research in human development often relies on composites, that is, composed variables such as indices. Their composite nature renders these variables inaccessible to conventional factor-centric psychometric validation techniques such as confirmatory factor analysis (CFA). In the context of human development research, there is currently no…

Multilevel structural equation models (MSEMs) are well suited for educational research because they accommodate complex systems involving latent variables in multilevel settings. Estimation using Croon's bias-corrected factor score (BCFS) path estimation has recently been extended to MSEMs and demonstrated promise with limited sample sizes. This…

Based on the instructional interaction principles outlined by Chen and Wang (2016) in third-generation distance learning, this study employs a recursive logical perspective on the evolution of the theory of interaction in distance education. It constructs a structural equation model to measure the mediating utility path of the learner's proactive…

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…

Transfer beliefs are understudied in the training transfer field, whereas structural equation modelling (SEM) has been a widely used technique to study transfer models. New methodologies are needed to study training transfer and network analysis (NA) has emerged as a new approach that provides a visual representation of a given network. We…

The study investigated the structural equation modelling of nine variables consisting of research undertaking, digi-tech construct (digital nativity, category of adoption of digital technologies, digital literacy, digital citizenship, statistical software anxiety, self-efficacy and knowledge) and researcher statistical software skills in the…

This study aimed to develop a structural equation model for ICT competency in administrators affecting school administration and propose implementation guidelines. The research involved two phases: model development and focus group discussions for guideline formulation. The sample included 310 educational administrators and department heads from…

Background: Science identity is widely regarded as a key predictor of students' persistence in STEM fields, while the brain drain in STEM fields is an urgent issue for countries to address. Based on previous studies, it is logical to suggest that epistemological beliefs about science and reflective thinking contribute to the development of science…

With the prevalence of missing data in social science research, it is necessary to use methods for handling missing data. One framework in which data with missing values can still be used for parameter estimation is the Bayesian framework. In this tutorial, different missing data mechanisms including Missing Completely at Random, Missing at…

A procedure for evaluating the average R-squared index for a given set of observed variables in an exploratory factor analysis model is discussed. The method can be used as an effective aid in the process of model choice with respect to the number of factors underlying the interrelationships among studied measures. The approach is developed within…