This article is concerned with the assumption of linear temporal development that is often advanced in structural equation modeling-based longitudinal research. The linearity hypothesis is implemented in particular in the popular intercept-and-slope model as well as in more general models containing it as a component, such as longitudinal…

Background: Structural Equation Modeling (SEM) is a powerful and broadly utilized statistical framework. Researchers employ these models to dissect relationships into direct, indirect, and total effects (Bollen, 1989). These models unpack the "black box" issues within cause-and-effect studies by examining the underlying theoretical…

Times of (post) health crisis, global unrest, and political turmoil, a reliance on conventional methods, which potentially lack radical imagination and future orientation, experimentation, and open-endedness, might not be enough. Furthermore, within the discourses of conventional qualitative inquiry, methodological subjects are often seen as…

A key aspect of engaging in a large participatory action research (PAR) project is ensuring that novice participant-researchers have a general understanding of the PAR methodology. Lead researchers experienced in action research cannot expect novice participant-researchers to engage fully with the literature on PAR, but rather need a simple way to…

GSCA Pro is free, user-friendly software for generalized structured component analysis structural equation modeling (GSCA-SEM), which implements three statistical methods for estimating models with factors only, models with components only, and models with both factors and components. This tutorial aims to provide step-by-step illustrations of how…

In the complex world of educational policy, causal inferences will be debated. As we review non-experimental designs in educational policy, we focus on how to clarify and focus the terms of debate. We begin by presenting the potential outcomes/counterfactual framework and then describe approximations to the counterfactual generated from the…

Researchers in behavioral sciences are often interested in longitudinal behavior change outcomes and the mechanisms that influence changes in these outcomes over time. The statistical models that are typically implemented to address these research questions do not allow for investigation of mechanisms of dynamic change over time. However, latent…

This paper looks at the tension between the desire to claim predictive ability for Agent-Based Models (ABMs) and its extreme difficulty for social and ecological systems, suggesting that this is the main cause for the continuance of a rhetoric of prediction that is at odds with what is achievable. Following others, it recommends that it is better…

Researchers continue to choose PCA in scale development and adaptation studies because it is the default setting and overestimates measurement quality. When PCA is utilized in investigations, the explained variance and factor loadings can be exaggerated. PCA, in contrast to the models given in the literature, should be investigated in…

Integration is a valuable yet underutilized process in scientific literatures, including the achievement motivation literature. In this piece, we advocate for and illustrate the benefits of giving integration a central place within the achievement motivation literature. We pay particular attention to the hierarchical model of achievement…

Quantile regression (QR) provides an alternative to linear regression (LR) that allows for the estimation of relationships across the distribution of an outcome. However, as highlighted in recent research on the motherhood penalty across the wage distribution, different procedures for conditional and unconditional quantile regression (CQR, UQR)…

Background: For decades, education researchers have relied on the work of Campbell, Cook, and Shadish to help guide their thinking about valid impact estimates in the social sciences (Campbell & Stanley, 1963; Shadish et al., 2002). The foundation of this work is the "validity typology" and its associated "threats to…

Principal leadership has been widely regarded as a powerful catalyst for school improvement and student learning. This article presents a multivariate meta-analysis of 42 empirical studies, published between 2000 and 2020, that examined the effects of principal leadership on student achievement in the United States. The focus is on the conceptual…

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…

Three quantitative methods are compared for their ability to understand different COVID-19 fatality ratios in 33 OECD countries. Linear regression provides a limited overview without sensitivity to the diversity of cases. Cluster Analysis and Dynamic Patterns Synthesis (DPS) gives scrutiny to the granularity of case similarities and differences,…