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…

Research questions regarding how, for whom, and where a treatment achieves its effect on an outcome have become increasingly valued in substantive research. Such questions can be answered by causal moderated mediation analysis, which assesses the heterogeneity of the mediation mechanism underlying the treatment effect across individual and…

Growth mixture models (GMMs) are prevalent for modeling unknown population heterogeneity via distinct latent classes. However, GMMs are riddled with convergence issues, often requiring researchers to atheoretically alter the model with cross-class constraints to obtain convergence. We discuss how within-class random effects in GMMs exacerbate…

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…

Psychologists are interested in whether friends and couples share similar personalities or not. However, no statistical models are readily available to test the association between personalities and social relations in the literature. In this study, we develop a statistical model for analyzing social network data with the latent personality traits…

Approaches to learning are a set of domain-general skills that encompass curiosity, persistence, planning, and engagement in group learning. These skills play a key role in preschoolers' learning and predict school readiness in math and language. Preschool science is a critical domain for early education and facilitates learning across domains.…

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…

The normal-distribution-based likelihood ratio statistic T[subscript ml] = nF[subscript ml] is widely used for power analysis in structural Equation modeling (SEM). In such an analysis, power and sample size are computed by assuming that T[subscript ml] follows a central chi-square distribution under H[subscript 0] and a noncentral chi-square…

The present study examines the extent to which participation in a 14-week professional development course designed to improve teacher-child interactions in the classroom moderated the relation between teacher-reported job stress and gains in observed teacher-child interaction quality from the beginning to the end of the intervention. Participants…

This study explored the background knowledge (BK) and reading comprehension (RC) relationship for struggling adult readers. Using confirmatory factor analyses, a single-factor BK model exhibited better fit than a two-factor model separating academic knowledge and general information, which indicates that BK represents a unidimensional construct…

A critical aspect of intervention research is investigating the active ingredients that underlie intensive interventions and their theories of change. This study explored the rate of instructional interactions within treatment groups to determine whether they offered explanatory power of an empirically validated Tier 2 kindergarten mathematics…

Despite increasing interest in sluggish cognitive tempo (SCT) in children, the field is stymied by the lack of a standard symptom set that can be used across studies. Without a standard symptom set, it is difficult to determine if differences across studies are due to methodological or sample differences, or simply the way SCT was measured. To…

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test--post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test…

We investigated direct and indirect effects of component skills on writing (DIEW) using data from 193 children in Grade 1. In this model, working memory was hypothesized to be a foundational cognitive ability for language and cognitive skills as well as transcription skills, which, in turn, contribute to writing. Foundational oral language skills…

We investigated component language and cognitive skills of oral language comprehension of narrative texts (i.e., listening comprehension). Using the construction--integration model of text comprehension as an overarching theoretical framework, we examined direct and mediated relations of foundational cognitive skills (working memory and…