Background & Context: Intersectionality theory posits that each individual's unique intersection of identity is integral to understanding their lived experience. Intersectionality theory also understands that social positions interact with oppression to influence an individual's lived experience (Bowleg, 2012; Collins, 2007; Crenshaw, 1989).…

Youth in the U.S. face a mental health crisis--one that has steadily worsened over the past 10 years (Centers for Disease Control, 2023). Youth with disabilities may experience increased mental health risk compared to their peers without disabilities. Recent national surveys and systematic reviews reveal that mental health risk may be elevated for…

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…

A central issue in nonexperimental studies is identifying comparable individuals to remove selection bias. One common way to address this selection bias is through propensity score (PS) matching. PS methods use a model of the treatment assignment to reduce the dimensionality of the covariate space and identify comparable individuals. parallel to…

Does receipt of School Improvement Grants (SIG) funding to implement a school intervention model have an impact on outcomes for low-performing schools? This study answers this question using a regression discontinuity design (RDD) that exploits cutoff values on the continuous variables used to define SIG eligibility tiers, comparing outcomes in…

The purpose of this study was to explore the use of robust variance estimation for combining commonly specified multiple regression models and for combining sample-dependent focal slope estimates from diversely specified models. The proposed estimator obviates traditionally required information about the covariance structure of the dependent…

The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…

The study is designed to demonstrate and test the utility of the proposed two-stage matching method compared to other analytic methods traditionally employed for multisite observational studies. More specifically, the study addresses the following research questions: (1) How do different specifications of the matching method influence covariate…

A central issue in nonexperimental studies is the identification of comparable individuals (e.g. students) to remove selection bias. One such increasingly common method to identify comparable individuals and address selection bias is the propensity score (PS). PS methods rely on a model of the treatment assignment to identify comparable…

One of the vexing problems in the analysis of SSD is in the assessment of the effect of intervention. Serial dependence notwithstanding, the linear model approach that has been advanced involves, in general, the fitting of regression lines (or curves) to the set of observations within each phase of the design and comparing the parameters of these…

Data from single case designs (SCDs) have traditionally been analyzed by visual inspection rather than statistical models. As a consequence, effect sizes have been of little interest. Lately, some effect-size estimators have been proposed, but most are either (i) nonparametric, and/or (ii) based on an analogy incompatible with effect sizes from…

Interest in variation in program impacts--How big is it? What might explain it?--has inspired recent work on the analysis of data from multi-site experiments. One critical aspect of this problem involves the use of random or fixed effect estimates to visualize the distribution of impact estimates across a sample of sites. Unfortunately, unless the…

Randomized controlled trials (RCTs) and regression discontinuity (RD) studies both provide estimates of causal effects. A major difference between the two is that RD only estimates local average treatment effects (LATE) near the cutoff point of the forcing variable. This has been cited as a drawback to RD designs (Cook & Wong, 2008).…

The purpose of this study is to develop an estimate of Adequate Yearly Progress (AYP) that will allow for reliable and valid comparisons among student subgroups, schools, and districts. A shrinkage-type estimator of AYP using the Bayesian framework is described. Using simulated data, the performance of the Bayes estimator will be compared to…

The purpose of this study is through Monte Carlo simulation to compare several propensity score methods in approximating factorial experimental design and identify best approaches in reducing bias and mean square error of parameter estimates of the main and interaction effects of two factors. Previous studies focused more on unbiased estimates of…