Structural equation modeling (SEM) and path analysis using composite-scores are distinct classes of methods for modeling the relationship of theoretical constructs. The two classes of methods are integrated in the partial-least-squares approach to structural equation modeling (PLS-SEM), which systematically generates weighted composites and uses…

Prior studies investigating the effects of non-normality in structural equation modeling typically induced non-normality in the indicator variables. This procedure neglects the factor analytic structure of the data, which is defined as the sum of latent variables and errors, so it is unclear whether previous results hold if the source of…

We examined the effect of estimation methods, maximum likelihood (ML), unweighted least squares (ULS), and diagonally weighted least squares (DWLS), on three population SEM (structural equation modeling) fit indices: the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the standardized root mean square residual…

Despite the prevalence of ordinal observed variables in applied structural equation modeling (SEM) research, limited attention has been given to model evaluation methods suitable for ordinal variables, thus providing practitioners in the field with few guidelines to follow. This study represents a first attempt to thoroughly examine the…

Investigations in technology acceptance in education has largely overlooked certain unique populations like students from the "Collège d'enseignement général et professionnel" (CEGEP) system. In studies examining CEGEP students' use of technology, the Technology Acceptance Model (TAM) perspective has not been taken into account, nor have…

The study analyzed the factorial and concurrent validity of the Student-Teacher Relationship Scale (STRS) using an exploratory structural equation modeling (ESEM) approach. Participants were 368 Italian children aged 3 to 6 (M = 4.60, SD = 0.98). The three-factor ESEM solution fit the data better than the classical confirmatory factor analysis…

Structural equation modeling (SEM) is one of the most popular multivariate statistical techniques in Turkish educational research. This study elaborates the SEM procedures employed by 75 educational research articles which were published from 2010 to 2015 in Turkey. After documenting and coding 75 academic papers, categorical frequencies and…

Spline (or piecewise) regression models have been used in the past to account for patterns in observed data that exhibit distinct phases. The changepoint or knot marking the shift from one phase to the other, in many applications, is an unknown parameter to be estimated. As an extension of this framework, this research considers modeling the…

Purpose: Adoption of latest technological advancements (e.g. lecture capture system) is a hallmark of market-driven private universities. Among many other distinguishing features, lecture capture system (LCS) is the one which is being offered to enhance the flexibility of learning environment for attracting executive business students. Majority of…

Higher education institutions typically express the quality of their degree programs by describing the qualities, skills, and understanding their students possess upon graduation. One promising instructional design approach to facilitate institutions' efforts to deliver graduates with the appropriate knowledge and competencies is curriculum…

Few practice-oriented courses are currently integrated into online learning platforms, such as OpenCourseWare, Khan Academy, and Massive Open Online Courses (MOOCs). It is worthwhile to explore how learners respond to information technology and new teaching methods when practice-oriented course are placed online. Therefore, this study probes…

We highlight critical conceptual and statistical issues and how to resolve them in conducting Satorra-Bentler (SB) scaled difference chi-square tests. Concerning the original (Satorra & Bentler, 2001) and new (Satorra & Bentler, 2010) scaled difference tests, a fundamental difference exists in how to compute properly a model's scaling correction…

In many psychological questionnaires the need to analyze empirical data raises the fundamental problem of possible fake or fraudulent observations in the data. This aspect is particularly relevant for researchers working on sensitive topics such as, for example, risky sexual behaviors and drug addictions. Our contribution presents a new…

Ordinal variables are common in many empirical investigations in the social and behavioral sciences. Researchers often apply the maximum likelihood method to fit structural equation models to ordinal data. This assumes that the observed measures have normal distributions, which is not the case when the variables are ordinal. A better approach is…

Relative fit indices using the null model as the reference point in computation may differ across estimation methods, as this article illustrates by comparing maximum likelihood, ordinary least squares, and generalized least squares estimation in structural equation modeling. The illustration uses a covariance matrix for six observed variables…