In this paper, we develop a mixed stochastic approximation expectation-maximization (MSAEM) algorithm coupled with a Gibbs sampler to compute the marginalized maximum a posteriori estimate (MMAPE) of a confirmatory multidimensional four-parameter normal ogive (M4PNO) model. The proposed MSAEM algorithm not only has the computational advantages of…

In this paper, we develop a mixed stochastic approximation expectation-maximization (MSAEM) algorithm coupled with a Gibbs sampler to compute the marginalized maximum a posteriori estimate (MMAPE) of a confirmatory multidimensional four-parameter normal ogive (M4PNO) model. The proposed MSAEM algorithm not only has the computational advantages of…

In the article "It's Just an Observation," Robinson and Wainer (Educational Psychology Review 35, Robinson, D., & Wainer, H. (2023). It's just an observation. Educational Psychology Review, 35(83), Published online: 14 August, 2023) lamented that educational psychology is moving toward the dark side of the quality continuum, with…

Cross-loadings are common in multiple-factor confirmatory factor analysis (CFA) but often ignored in measurement invariance testing. This study examined the impact of ignoring cross-loadings on the sensitivity of fit measures (CFI, RMSEA, SRMR, SRMRu, AIC, BIC, SaBIC, LRT) to measurement noninvariance. The manipulated design factors included the…

This note demonstrates that measurement invariance does not guarantee meaningful and valid group comparisons in multiple-population settings. The article follows on a recent critical discussion by Robitzsch and Lüdtke, who argued that measurement invariance was not a pre-requisite for such comparisons. Within the framework of common factor…

A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals…

Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…

The Vocational Identity Status Assessment (VISA) is one of the instruments that can be used to assess vocational identity. Conceptually, VISA consists of six sub-dimensions and has been validated using factor analysis. This study provides a factor structure test of the Indonesian version of VISA using the exploratory structural equation modeling…

The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…

Urbanization, vocational education, and industry in China have been influenced by policy and economic changes. This article outlines potential solutions for the integrated development of urbanization, vocational education, and industry in China. By integrating the development ideas of the triple helix model based on international related research…

Purpose: Aging increases risk for hearing loss, cognitive decline, and social isolation; however, the nature of their interconnection remains unclear. This study examined the interplay between age-related hearing loss, cognitive decline, and social isolation in adults by testing the ability to understand speech in background noise, a challenge…

The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model…

Latent change score (LCS) models are a powerful class of structural equation modeling that allows researchers to work with latent difference scores that minimize measurement error. LCS models define change as a function of prior status, which makes it well-suited for modeling developmental theories or processes. In LCS models, like other latent…

Longitudinal research is often interested in identifying correlates of heterogeneity in change. This paper compares three approaches for doing so: the mixed-effects model (latent growth curve model), the growth mixture model, and structural equation model trees. Each method is described, with special focus given to how each structures…

This theoretical article proposes a unified framework of analysis for the constructs of intelligence and creativity. General definitions for intelligence and creativity are provided, allowing fair comparisons between the two context-embedded constructs. A novel taxonomy is introduced to classify the contexts in which intelligent and/or creative…