Purpose: A literature research conducted in education and agricultural education journals published during a period of 10 years revealed that 98% of the studies used parametric analyses. In general, model assumptions were not tested, and statistical criteria were not followed to apply the parametric approach. The objective of this paper is to…

Dominance analysis (DA) is a very useful tool for ordering independent variables in a regression model based on their relative importance in explaining variance in the dependent variable. This approach, which was originally described by Budescu, has recently been extended to use with structural equation models examining relationships among latent…

The number of clinical prediction models sharing the same prediction task has increased in the medical literature. However, evidence synthesis methodologies that use the results of these prediction models have not been sufficiently studied, particularly in the context of meta-analysis settings where only summary statistics are available. In…

Questionnaires inquiring about psychopathology symptoms often produce data with excess zeros or the equivalent (e.g., none, never, and not at all). This type of zero inflation is especially common in nonclinical samples in which many people do not exhibit psychopathology, and if unaccounted for, can result in biased parameter estimates when…

Examining the blended learning (b-learning) acceptance is not a new research topic, and it has been tackled by many scholars. Nevertheless, the analysis of information systems (IS) models that are used to study the acceptance of b-learning is regarded as a topic of great importance. To examine these models and afford scholars a holistic view of…

Translational research (TR) is the process of bringing innovations from basic science into applied science, usually referring to the practice of medicine. It has been assumed that cross-disciplinary collaboration, or interdisciplinarity research (IDR), is essential to translation. Yet there is a gap in the literature regarding the interaction…

Observable data in empirical social and behavioral science studies are often categorical (i.e., binary, ordinal, or nominal). When categorical data are outcomes, they fail to maintain the scale and distributional properties of linear regression and factor analysis. Attempting to estimate model parameters for categorical outcome data with the…

Teacher absenteeism has high individual and societal costs and triggers a vicious cycle by increasing teacher absenteeism for the remaining teachers. Moreover, teachers' non-attendance disrupts the learning process and affects student motivation and achievement. Teacher absenteeism further exacerbates the increasing teacher shortage observed in…

This paper discusses investigations in science education addressing the nonlinear dynamical hypothesis. Learning science is a suitable field for applying interdisciplinary research and predominately for testing psychological theories. It was demonstrated that in this area the paradigm of complexity and nonlinear dynamics have offered theoretical…

Course-based undergraduate research experiences (CUREs) represent an economical and practical way for institutions to equitably offer research experiences to large numbers of students. Although the benefits of CUREs are well documented, most CURE models are not guided by theory and are discipline specific, which limits their application. We used a…

Introduction: Previous studies suggest that many systematic reviews contain meta-analyses that display temporal trends, such as the first study's result being more extreme than later studies' or a drift in the pooled estimate. We assessed the extent and characteristics of temporal trends using all Cochrane intervention reports published 2008-2012.…

In this study, international research collaboration (IRC) and international research orientation (IRO) have been studied at the micro-level of individual academics from the university sector (N = 8,466, 11 European systems). Both were studied cross-nationally, cross-disciplinarily, and cross-generationally. This study differs from most existing…

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…

The present study illustrates the utility of applying multilevel mixture models in educational research, using data on the homework behavior of 1,812 Swiss eighth-grade students in French as a second language. A previous person-centered study identified 5 homework learning types characterized by different patterns of high or low homework time and…

Purpose: We aim to identify the most accurate model for predicting adolescent (Grade 9) reading difficulties (RD) in reading fluency and reading comprehension using 17 kindergarten-age variables. Three models (neural networks, linear, and mixture) were compared based on their accuracy in predicting RD. We also examined whether the same or a…