We consider a class of multiple-group individually-randomized group trials (IRGTs) that introduces a (partially) cross-classified structure in the treatment condition (only). The novel feature of this design is that the nature of the treatment induces a clustering structure that involves two or more non-nested groups among individuals in the…

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…

Background: Education scientists are increasingly interested in constructing interventions that are adaptive over time to suit the evolving needs of students, classrooms, or schools. Such "adaptive interventions" (also referred to as dynamic treatment regimens or dynamic instructional regimes) determine which treatment should be offered…

Background: Meta-analysis refers to the statistical methods employed to combine results of several empirical studies in a topic of interest (Hedges & Olkin, 1985). Meta-analysis is often included in literature review studies to quantitatively analyze data from a collection of studies (Valentine et al., 2010). The statistical power of a…

In a randomized controlled trial (RCT), some subjects assigned to the treatment condition may not fully comply. Often there is interest in the effect of the treatment within the "principal stratum" of subjects who would comply if assigned to treatment. However, it is unknown which control subjects would have complied if treated and which…

Background: This paper develops a new method to estimate quasi-experimental evaluation models when it is necessary to control for measurement error in predictors and individual assignment to the treatment group is based on these same fallible variables. A major methodological finding of the study is that standard methods of estimating models that…

Background and Context: In 2016, our team designed and implemented a cluster-randomized trial of a school-based empowerment training program, targeting adolescent girls in Nairobi, Kenya (Baiocchi et al., 2019; Rosenman et al., 2020). In that study, the primary outcome was the experience of sexual violence in the prior year. Participants disclosed…

Background: Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs)…

Lord's paradox arises from the conflicting inferences obtained from two alternative approaches that are typically used in evaluating the treatment effect using a pre-post test design. The two main approaches for analyzing such data are: (1) to regress the change from pretest to posttest on the treatment indicator (change score approach; CS); (2)…

We develop a structural after measurement (SAM) method for structural equation models (SEMs) that accommodates missing data. The results show that the proposed SAM missing data estimator outperforms conventional full information (FI) estimators in terms of convergence, bias, and root-mean-square-error in small-to-moderate samples or large samples…

Background/Context: School principals have long played a central role in managing building operations and supervising school employees. Over the past two decades, however, policy developments--including site-based management, external accountability measures, and teacher evaluation systems--have increased expectations that principals also improve…

Background: Efficacy trials in education often possess a motivating theory of change: how and why should the desired improvement in outcomes occur as a consequence of the intervention? In scenarios with repeated measurements, certain subgroups may be more or less likely to manifest a treatment effect; the theory of change (TOC) provides guidance…

This paper develops models to measure growth in student achievement with a focus on the possibility of differential growth in achievement for low and high-achieving students. We consider a gap-closing model that evaluates the degree to which students in a target group -- students in the bottom quartile of measured achievement -- perform better…

Over the past decade, states and districts have updated teacher evaluation systems in response to federal incentives, such as waivers to No Child Left Behind and grants from Race to the Top. The use of multiple measures, however, raises an important issue for policymakers and practitioners: to what extent should different measures of a teacher's…

Valid and reliable measurement of unobserved latent variables is essential to understanding and improving education. A common and persistent approach to assessing latent constructs in education is the use of rater inferential judgment. The purpose of this study is to develop high-dimensional explanatory random item effects models designed for…