A two-level data set can be structured in either long format (LF) or wide format (WF), and both have corresponding SEM approaches for estimating multilevel models. Intuitively, one might expect these approaches to perform similarly. However, the two data formats yield data matrices with different numbers of columns and rows, and their "cols :…

Researchers tasked with understanding the effects of educational technology innovations face the challenge of providing evidence of causality. Given the complexities of studying learning in authentic contexts interwoven with technological affordances, conducting tightly-controlled randomized experiments is not always feasible nor desirable. Today,…

In parallel process latent growth curve mediation models, the mediation pathways from treatment to the intercept or slope of outcome through the intercept or slope of mediator are often of interest. In this study, we developed causal mediation analysis methods for these mediation pathways. Particularly, we provided causal definitions and…

Individual religiosity measures are used by researchers to describe and compare individuals and societies. However, the cross-cultural comparability of the measures has often been questioned but rarely empirically tested. In the current study, we examined the cross-national measurement invariance properties of generalized individual religiosity in…

This study examined the false positive (FP) rates and sensitivity of Bayesian fit indices to structural misspecification in Bayesian structural equation modeling. The impact of measurement quality, sample size, model size, the magnitude of misspecified path effect, and the choice or prior on the performance of the fit indices was also…

Intensive longitudinal data has been widely used to examine reciprocal or causal relations between variables. However, these variables may not be temporally aligned. This study examined the consequences and solutions of the problem of temporal misalignment in intensive longitudinal data based on dynamic structural equation models. First the impact…

Generalized structured component analysis (GSCA) is a multivariate method for specifying and examining interrelationships between observed variables and components. Despite its data-analytic flexibility honed over the decade, GSCA always defines every component as a linear function of observed variables, which can be less optimal when observed…

This study uses one-step meta-analytic structural equation modelling to delve into the technology acceptance model's (TAM) application within education, assessing perceived usefulness, ease of use, intentions to use, and actual technology use. It synthesises previous findings to validate the TAM's effectiveness and uncover the model's predictive…

Despite the burgeoning adoption of informal learning in people's daily lives, the actual effects of informal learning activities, especially technology-related informal learning activities, are much less reported than those of formal learning. Furthermore, there is a notable lack of research on the effects of technology-related informal…

Structural equation models offer a valuable tool for delineating the complicated interrelationships among multiple variables, including observed and latent variables. Over the last few decades, structural equation models have successfully analyzed complete and right-censored survival data, exemplified by wide applications in psychological, social,…

This study investigated the underlying mechanism between bullying victimization and depressive symptoms via social trust cross-sectionally and longitudinally among 4,548 early adolescents at T1 and 4,484 adolescents at T2 from rural areas in Guizhou, China. Correlational data showed that all forms of bullying victimization at T1 showed negative…

Blended collaborative learning has emerged as an effective pedagogical model that integrates face-to-face and online learning environments, offering a dynamic platform for deep learning--characterized by critical thinking, knowledge synthesis, and application. However, existing research offers mixed findings on how blended collaborative learning…

Based on the self-determination theory (SDT), this evaluates the effects of generative artificial intelligence (Gen-AI) on learning performance within China's education sector, emphasizing the roles of social interaction, utilitarian benefit, knowledge acquisition, and epistemic curiosity. The study employs a dual method, using PLS-SEM and fsQCA…

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…

Background: Poor sleep is commonplace among traditional entry university students. Lifestyle modifications, such as time management behaviors, may improve sleep quality by allocating sufficient time for sleep and mitigating stress-associated sleep latency inefficiencies. Purpose: The purpose of our study was to evaluate time management behaviors…