Although generalizability theory (GT) designs typically are analyzed using analysis of variance (ANOVA) procedures, they also can be integrated into structural equation models (SEMs). In this tutorial, we review basic concepts for conducting univariate and multivariate GT analyses and demonstrate advantages of doing such analyses within SEM…

Multivariate analysis of variance (MANOVA) is widely used to test the null hypothesis of equal multivariate means across 2 or more groups. MANOVA rests upon an assumption that error terms are independent of one another, which can be violated if individuals are clustered or nested within groups, such as schools. Ignoring such nesting can result in…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

The latent growth model (LGM) in structural equation modeling (SEM) may be extended to allow for the modeling of associations among multiple latent growth trajectories, resulting in a multiple domain latent growth model (MDLGM). While the MDLGM is conceived as a more powerful multivariate analysis technique, the examination of its methodological…

Measuring values in sociological research sometimes involves the use of ranking data. A disadvantage of a ranking assignment is that the order in which the items are presented might influence the choice preferences of respondents regardless of the content being measured. The standard procedure to rule out such effects is to randomize the order of…

The social relations model (SRM) is a mathematical model that can be used to analyze interpersonal judgment and behavior data. Typically, the SRM is applied to one (i.e., univariate SRM) or two variables (i.e., bivariate SRM), and parameter estimates are obtained by employing an analysis of variance method. Here, we present an extension of the SRM…

This book presents different data collection and representation techniques: elementary descriptive statistics, confirmatory statistics, multivariate approaches and statistical modeling. It exposes the possibility of giving more robustness to the classical methodologies of education sciences by adding a quantitative approach. The fundamentals of…

Evaluation is an important aspect of science and is receiving increasing attention in science education. The present study investigated (1) changes to plausibility judgments and knowledge as a result of a series of instructional scaffolds, called model-evidence link activities, that facilitated evaluation of scientific and alternative models in…

Value-added assessment methods have been criticized by researchers and policy makers for a number of reasons. One issue includes the sensitivity of model results across different outcome measures. This study examined the utility of incorporating multivariate latent variable approaches within a traditional value-added framework. We evaluated the…

The purpose of this research was to identify the competencies of educational technologists by surveying the professionals within the field. The Educational Technology Competency Survey (ETCS) developed in this research was based on a conceptual framework that emphases the definition of educational technology and associated knowledge, skill, and…

This study aims to apply the model principal component analysis to reduce multicollinearity on variable currency exchange rate in eight countries in Asia against US Dollar including the Yen (Japan), Won (South Korea), Dollar (Hong Kong), Yuan (China), Bath (Thailand), Rupiah (Indonesia), Ringgit (Malaysia), Dollar (Singapore). It looks at yield…

This study examined an extended theory of planned behaviour (TPB) model that specified factors affecting students' intentions to collaborate online for group work. Past behaviour, past experience and actual behavioural control were incorporated in the extended TPB model. The mediating roles of attitudes, subjective norms and perceived behavioural…

Principal component analysis is an important statistical technique for dimension reduction and exploratory data analysis. However, it is not robust to outliers and may obfuscate important data structure such as clustering. We propose a version of principal component analysis based on the robust L2E method. The technique seeks to find the principal…

One of the most common questions asked within school psychology research concerns the relationship between an intervention (independent variable) and an outcome (dependent variable). For example, say a researcher is interested in the effect of a cognitive-behavioral intervention (independent variable) on student depression (dependent variable).…

The research was designed to examine the effects of question setting using different conditions into 10 sets on the validity of structural equation modeling for factors affecting job morale. The data was collected from 690 personnel working in regional Statistical Offices around Thailand by using cluster random sampling. The tool used in…