This article is concerned with a subset of numerically stable and scalable algorithms useful to support computationally complex psychometric models in the era of machine learning and massive data. The subset selected here is a core set of numerical methods that should be familiar to computational psychometricians and considers whitening transforms…

In real-world situations, multidimensional data may appear on large-scale tests or psychological surveys. The purpose of this study was to investigate the effects of the quantity and magnitude of cross-loadings and model specification on item parameter recovery in multidimensional Item Response Theory (MIRT) models, especially when the model was…

One of the aims of the current study is to specify the model providing the best fit to the data among the exploratory, the bifactor exploratory and the confirmatory structural equation models. The study compares the three models based on the model data fit statistics and item parameter estimations (factor loadings, cross-loadings, factor…

Purpose and Background: Despite the flexibility of multilevel structural equation modeling (MLSEM), a practical limitation many researchers encounter is how to effectively estimate model parameters with typical sample sizes when there are many levels of (potentially disparate) nesting. We develop a method-of-moment corrected maximum likelihood…

In real-world situations, multidimensional data may appear on large-scale tests or attitudinal surveys. A simple structure, multidimensional model may be used to evaluate the items, ignoring the cross-loading of some items on the secondary dimension. The purpose of this study was to investigate the influence of structure complexity magnitude of…

The semi-generalized partial credit model (Semi-GPCM) has been proposed as a unidimensional modeling method for handling not applicable scale responses and neutral scale responses, and it has been suggested that the model may be of use in handling missing data in scale items. The purpose of this study is to evaluate the ability of the…

The authors investigated how work-family balance mediated the relationship between personality traits, gender roles, social support, and psychosocial adjustment. Data were collected from 243 married international graduate students (MIGSs) studying in the United States. Results of structural equation modeling indicated that personality traits…

Meta-analysis plays a key role in combining studies to obtain more reliable results. In social, behavioral, and health sciences, measurement units are typically not well defined. More meaningful results can be obtained by standardizing the variables and via the analysis of the correlation matrix. Structural equation modeling (SEM) with the…

The purpose of this study was to investigate the effect of a leader's social intelligence (SI) on an employee's perception of interpersonal justice by considering the mediating role of shared leadership. Conceptual model and research hypotheses have been developed by the Marlowe's SI model (1986), and the theory of shared leadership and…

This paper investigates the direct and indirect ties between various leadership styles, namely, instructional, transformational, transactional, and laissez-faire leadership, and the instructional practices of teachers by applying a structural equation model. For this purpose, we analyzed survey data of n = 3,746 teachers from 126 schools collected…

Middle school has been documented as the period in which a drop in students' science interest and achievement occurs. This trend indicates a lack of motivation for learning science; however, little is known about how different aspects of motivation interact with student engagement and science learning outcomes. This study examines the…

The traditional approach to estimating the consistency of school effects across subject areas and the stability of school effects across time is to fit separate value-added multilevel models to each subject or cohort and to correlate the resulting empirical Bayes predictions. We show that this gives biased correlations and these biases cannot be…

Meta-analytic structural equation modeling (MASEM) involves fitting models to a common population correlation matrix that is estimated on the basis of correlation coefficients that are reported by a number of independent studies. MASEM typically consist of two stages. The method that has been found to perform best in terms of statistical…

This research aimed to construct and validate the School Conflict Negotiation Effectiveness Questionnaire (SCNEQ). This objective is both based on the increasing relevance of the area of constructive conflict management in schools and also in the scarcity of instruments that try to measure these dimensions in the educational context. We used two…

Lord's Wald test for differential item functioning (DIF) has not been studied extensively in the context of the multidimensional item response theory (MIRT) framework. In this article, Lord's Wald test was implemented using two estimation approaches, marginal maximum likelihood estimation and Bayesian Markov chain Monte Carlo estimation, to detect…