In this article, we extend Liao's test for across-group comparisons of the fixed effects from the generalized linear model to the fixed and random effects of the generalized linear mixed model (GLMM). Using as our basis the Wald statistic, we developed an asymptotic test statistic for across-group comparisons of these effects. The test can be…

Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or might instead be a methodological artifact reflecting item response theory (IRT) model misspecification.…

The purpose of the study is to analyze the affective traits that affect mathematics achievement through Structural Equation Modeling (SEM) as a traditional regression model and Multivariate Adaptive Regression Splines (MARS), as one of the data mining methods. Structural Equation Modeling, one of the regression-based methods, is quite popular for…

For many countries, inequitable access to rigorous content and instruction at the early grades leads to the low academic performance for students with fewer resources at home. One way to assess these inequities, and identify possible mediators, is to consider the role of instructional leadership as a means for schools to set educational goals for…

Detection of students' ability levels is one of the common aims in educational studies. Cognitive Diagnosis Modeling approach has been used recently for the purpose of ability level detection by defined Q-matrices. To evaluate students' strengths and weaknesses, determine their mastery skills, and design instructions and interventions in learning…

Recognizing the limitations of the existing frameworks and models applied to estimate the learning loss caused by COVID-19 across the world by different studies, and the urgent need for estimating such loss at the different education levels, this paper, employs the Education Value Chain Analysis ( EVCA) approach as a new paradigm, attempts to…

Data mining has been successfully used by financial and retail companies since the mid-1960's to create predictive models and reveal unexpected relationships. However, it remains underutilized as a tool in educational research. Large-scale standardized assessment programs such as the Trends in International Mathematics and Science Study (TIMSS)…

An aggregation strategy is proposed to potentially address practical limitation related to computing resources for two-level multidimensional item response theory (MIRT) models with large data sets. The aggregate model is derived by integration of the normal ogive model, and an adaptation of the stochastic approximation expectation maximization…

This article presents a new perspective on measuring gender differences in the large-scale assessment study Trends in International Science Study (TIMSS). The suggested empirical model is directly based on the theoretical competence model of the domain mathematics and thus includes the interaction between content and cognitive sub-competencies.…

In this study, the Trends in International Mathematics and Science Study 2007 data were used to build mathematics achievement models of fourth graders in two East Asian school systems: Hong Kong and Singapore. In each school system, eight variables at student level and nine variables at school/class level were incorporated to build an achievement…

The link between reading and mathematics achievement is well known, and an important question is whether readability factors in mathematics problems are differentially impacting student groups. Using 20 years of data from the National Assessment of Educational Progress and the Trends in International Mathematics and Science Study, we examine how…

The present paper aims to discuss how data from international large-scale assessments (ILSAs) can be utilized and combined, even with other existing data sources, in order to monitor educational outcomes and study the effectiveness of educational systems. We consider different purposes of linking data, namely, extending outcomes measures,…

This tutorial addresses possible sources of confusion in interpreting trait scores from the bifactor model. The bifactor model may be used when subscores are desired, either for formative feedback on an achievement test or for theoretically different constructs on a psychological test. The bifactor model is often chosen because it requires fewer…

Background: Large-scale cross-national studies designed to measure student achievement use different social, cultural, economic and other background variables to explain observed differences in that achievement. Prior to their inclusion into a prediction model, these variables are commonly scaled into latent background indices. To allow…

The present study investigated (a) how a latent profile analysis based on representative data of N = 74,868 4th graders from 17 European countries would cluster the students on the basis of their reading, mathematics, and science achievement test scores; (b) whether there would be gender differences at various competency levels, especially among…