Network models of the WAIS-IV based on regularized partial correlation matrices have been reported to outperform latent variable models based on uncorrected correlation matrices. The present study sought to compare network and latent variable models using both partial and uncorrected correlation matrices with both types of models. The results show…

In this article, I present a new multivariate regression model for analyzing outcomes with network dependence. The model is capable to account for two types of outcome dependence including the mean dependence that allows the outcome to depend on selected features of a known dependence network and the error dependence that allows the outcome to be…

This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…

Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…

Objective: To use egocentric network analysis to understand how composition and structure of egonetworks relate to violence victimization among college students. Participants: 697 students from a large southeastern university completed online surveys. Methods: Hierarchical logistic regression analyses assessed the relationship between egocentric…

In an age of environmental crisis, financial instability, widespread migration, and political extremism, the case for critical literacy is pressing. Navigating criticality in the digital age, however, is challenging, not least because digital media, digital devices, and digital architectures are implicated in broader social, cultural, commercial,…

Randomised controlled trials of cancer treatments typically report progression free survival (PFS) and overall survival (OS) outcomes. Existing methods to synthesise evidence on PFS and OS either rely on the proportional hazards assumption or make parametric assumptions which may not capture the diverse survival curve shapes across studies and…

Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…

Purpose: We assess farm technology adoption in an integrated analysis of social networks and innovation in plantain production in Ghana. The paper explores the strength of social networks in the agricultural innovation systems (AISs) and the effect of AISs on adoption of improved farm technology. Methodology/Approach: The paper uses social network…

Purpose: This study aimed to explore how an adapted theoretical framework by networking two theories could help document teachers' collective learning through lesson study. Design/methodology/approach: Interconnected Model of Teacher Professional Growth (IMPG) and Documentational Approach to Didactics (DAD) has been used individually to document…

We examined 3 different network models of representing semantic knowledge (5,018-word directed and undirected step distance networks, and an association-correlation network) to predict lexical priming effects. In Experiment 1, participants made semantic relatedness judgments for word pairs with varying path lengths. Response latencies for…

The structure of academic self-concept (ASC) is assumed to be multidimensional and hierarchical. This methodological review considers the most central models depicting the structure of ASC: a higher-order factor model, the Marsh/Shavelson model, the nested Marsh/Shavelson model, a bifactor representation based on exploratory structural equation…

Time-course model-based network meta-analysis (MBNMA) has been proposed as a framework to combine treatment comparisons from a network of randomized controlled trials reporting outcomes at multiple time-points. This can explain heterogeneity/inconsistency that arises by pooling studies with different follow-up times and allow inclusion of studies…

This paper provides a tutorial on epistemic network analysis (ENA), a novel method for identifying and quantifying connections among elements in coded data and representing them in dynamic network models. Such models illustrate the structure of connections and measure the strength of association among elements in a network, and they quantify…

Currently available (classical) testing procedures for the network autocorrelation can only be used for falsifying a precise null hypothesis of no network effect. Classical methods can be neither used for quantifying evidence for the null nor for testing multiple hypotheses simultaneously. This article presents flexible Bayes factor testing…