Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…

Combining observational and experimental data for causal inference can improve treatment effect estimation. However, many observational data sets cannot be released due to data privacy considerations, so one researcher may not have access to both experimental and observational data. Nonetheless, a small amount of risk of disclosing sensitive…

In multisite trials, learning about treatment effect variation across sites is critical for understanding where and for whom a program works. Unadjusted comparisons, however, capture "compositional" differences in the distributions of unit-level features as well as "contextual" differences in site-level features, including…

Exploratory structural equation modeling (ESEM) is an approach for analysis of latent variables using exploratory factor analysis to evaluate the measurement model. This study compared ESEM with two dominant approaches for multiple regression with latent variables, structural equation modeling (SEM) and manifest regression analysis (MRA). Main…

In causal mediation analysis, the definitions of the natural direct and indirect effects involve potential outcomes that can never be observed, so-called a priori counterfactuals. This conceptual challenge translates into issues in identification, which requires strong and often unverifiable assumptions, including sequential ignorability.…

Varying methods for evaluating the outcomes of single case research designs (SCD) are currently used in reviews and meta-analyses of interventions. Quantitative effect size measures are often presented alongside visual analysis conclusions. Six measures across two classes--overlap measures (percentage non-overlapping data, improvement rate…

Inferring causal effects of treatments is a central goal in many disciplines. The potential outcomes framework is a main statistical approach to causal inference, in which a causal effect is defined as a comparison of the potential outcomes of the same units under different treatment conditions. Because for each unit at most one of the potential…

Dialogism provides the grounds for building a comprehensive model of discourse and it is focused on the multiplicity of perspectives (i.e., voices). Dialogism can be present in any type of text, while voices become themes or recurrent topics emerging from the discourse. In this study, we examine the extent that differences between…

We compared students' performance on a paper-based test (PBT) and three computer-based tests (CBTs). The three computer-based tests used different test navigation and answer selection features, allowing us to examine how these features affect student performance. The study sample consisted of 9,698 fourth through twelfth grade students from across…

A growing number and proportion of students rely on student loans to assist with the costs of postsecondary education. Yet little is known about how first-generation students use federal loans to finance their education. In this article, we examine each of the decisions that culminate in student indebtedness: the decision to apply for aid, whether…

Growth curve modeling provides a general framework for analyzing longitudinal data from social, behavioral, and educational sciences. Bayesian methods have been used to estimate growth curve models, in which priors need to be specified for unknown parameters. For the covariance parameter matrix, the inverse Wishart prior is most commonly used due…

How do toddlers learn the names of geometric forms? Previous work suggests that preschoolers have fragmentary knowledge and that defining properties are not understood until well into elementary school. The current study investigated when children first begin to understand shape names and how they apply those labels to unusual instances. We tested…

The Florida College and Career Readiness Initiative (FCCRI) was a statewide policy requiring college readiness testing and participation in college readiness courses for high school students. We used regression discontinuity to compare outcomes for students scoring just above and below test score cutoffs for assignment to FCCRI. We also examined…

The importance of social-emotional competence, executive functioning, and behavioural recognition of patterns by young children is receiving increased attention from researchers, schools, parents, and teachers due to the beneficial outcomes of children who have skills in each. This paper presents studies of the correlations between these variables…

Research on school leadership suggests that both principal and teacher leadership are important for school improvement. However, few studies have studied the interaction of principal and teacher leadership as separate but linked systems in how they relate to student outcomes. In this study, we examine how leadership pathways are related in the…